Learning and Development Officer Jobs
Learning and Development Officer jobs are open across corporate enterprises, healthcare systems, government agencies, and nonprofits, at every level from entry-level coordinator to senior director, with specializations in instructional design, talent management, and leadership development programs. Find a role that fits below and apply directly.
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Showing 5 of 4,292+ Learning and Development Officer jobs
Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking a hands-on people leader for Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer people leader, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One.
What You’ll Do:
- Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
- Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
- Lead large-scale ML initiatives with the customer in mind
- Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
- Optimize data pipelines to feed ML models
- Use programming languages like Python, Scala, or Java
- Evangelize best practices in all aspects of the engineering and modeling lifecycles
- Recruit, nurture, and retain top engineering talent
- Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
- Recruit, nurture, and retain top engineering talent
- Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community
Basic Qualifications:
- Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 3 years of people leadership experience
- At least 8 years of experience programming with Python, Java, Golang, or C++
- At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
- At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
- At least 5 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems
Preferred Qualifications:
- Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
- 5+ years of experience managing and leading an engineering team
- 3+ years of experience architecting and designing resilient, large-scale, production machine learning systems from data preparation, to model training, and inference
- 5+ years of experience optimizing ML algorithms, configurations, and infrastructure
- 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)
- 7+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
- Ability to communicate complex technical concepts clearly to a variety of audiences
- Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
- Experience hiring and developing high-performing ML engineers with an inspiring leadership style
- Highly developed interpersonal, presentation, and communications skills
- Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $269,100 - $307,200 for Director, Machine Learning EngineerNew York, NY: $293,600 - $335,100 for Director, Machine Learning Engineer
San Francisco, CA: $293,600 - $335,100 for Director, Machine Learning Engineer
San Jose, CA: $293,600 - $335,100 for Director, Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Director, Machine Learning EngineerDo you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking a hands-on people leader for Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer people leader, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One.
What You’ll Do:
- Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
- Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
- Lead large-scale ML initiatives with the customer in mind
- Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
- Optimize data pipelines to feed ML models
- Use programming languages like Python, Scala, or Java
- Evangelize best practices in all aspects of the engineering and modeling lifecycles
- Recruit, nurture, and retain top engineering talent
- Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
- Recruit, nurture, and retain top engineering talent
- Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community
Basic Qualifications:
- Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 3 years of people leadership experience
- At least 8 years of experience programming with Python, Java, Golang, or C++
- At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
- At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
- At least 5 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems
Preferred Qualifications:
- Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
- 5+ years of experience managing and leading an engineering team
- 3+ years of experience architecting and designing resilient, large-scale, production machine learning systems from data preparation, to model training, and inference
- 5+ years of experience optimizing ML algorithms, configurations, and infrastructure
- 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)
- 7+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
- Ability to communicate complex technical concepts clearly to a variety of audiences
- Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
- Experience hiring and developing high-performing ML engineers with an inspiring leadership style
- Highly developed interpersonal, presentation, and communications skills
- Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $269,100 - $307,200 for Director, Machine Learning EngineerNew York, NY: $293,600 - $335,100 for Director, Machine Learning Engineer
San Francisco, CA: $293,600 - $335,100 for Director, Machine Learning Engineer
San Jose, CA: $293,600 - $335,100 for Director, Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking a hands-on people leader for Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer people leader, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One.
What You’ll Do:
- Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
- Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
- Lead large-scale ML initiatives with the customer in mind
- Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
- Optimize data pipelines to feed ML models
- Use programming languages like Python, Scala, or Java
- Evangelize best practices in all aspects of the engineering and modeling lifecycles
- Recruit, nurture, and retain top engineering talent
- Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
- Recruit, nurture, and retain top engineering talent
- Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community
Basic Qualifications:
- Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 3 years of people leadership experience
- At least 8 years of experience programming with Python, Java, Golang, or C++
- At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
- At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
- At least 5 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems
Preferred Qualifications:
- Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
- 5+ years of experience managing and leading an engineering team
- 3+ years of experience architecting and designing resilient, large-scale, production machine learning systems from data preparation, to model training, and inference
- 5+ years of experience optimizing ML algorithms, configurations, and infrastructure
- 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)
- 7+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
- Ability to communicate complex technical concepts clearly to a variety of audiences
- Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
- Experience hiring and developing high-performing ML engineers with an inspiring leadership style
- Highly developed interpersonal, presentation, and communications skills
- Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $269,100 - $307,200 for Director, Machine Learning EngineerNew York, NY: $293,600 - $335,100 for Director, Machine Learning Engineer
San Francisco, CA: $293,600 - $335,100 for Director, Machine Learning Engineer
San Jose, CA: $293,600 - $335,100 for Director, Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Director, Machine Learning EngineerDo you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking a hands-on people leader for Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer people leader, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One.
What You’ll Do:
- Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams
- Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems
- Lead large-scale ML initiatives with the customer in mind
- Leverage cloud-based architectures and technologies to deliver optimized ML models at scale
- Optimize data pipelines to feed ML models
- Use programming languages like Python, Scala, or Java
- Evangelize best practices in all aspects of the engineering and modeling lifecycles
- Recruit, nurture, and retain top engineering talent
- Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
- Recruit, nurture, and retain top engineering talent
- Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community
Basic Qualifications:
- Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
- At least 3 years of people leadership experience
- At least 8 years of experience programming with Python, Java, Golang, or C++
- At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
- At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
- At least 5 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems
Preferred Qualifications:
- Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
- 5+ years of experience managing and leading an engineering team
- 3+ years of experience architecting and designing resilient, large-scale, production machine learning systems from data preparation, to model training, and inference
- 5+ years of experience optimizing ML algorithms, configurations, and infrastructure
- 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)
- 7+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
- Ability to communicate complex technical concepts clearly to a variety of audiences
- Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
- Experience hiring and developing high-performing ML engineers with an inspiring leadership style
- Highly developed interpersonal, presentation, and communications skills
- Driving impacts in the ML industry through conference presentations, papers, blog posts, open source contributions or patents
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $269,100 - $307,200 for Director, Machine Learning EngineerNew York, NY: $293,600 - $335,100 for Director, Machine Learning Engineer
San Francisco, CA: $293,600 - $335,100 for Director, Machine Learning Engineer
San Jose, CA: $293,600 - $335,100 for Director, Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Learning and Development Officer Jobs by Experience Level
See All 4,292+ Learning and Development Officer Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsLearning and Development Officer Job Market
Who's Hiring
- Apple202
- TikTok99
- Meta56
- Uber47
- Amazon47
Top Industries Hiring
- Technology & Software352
- Education64
- Artificial Intelligence64
- Electronics & Hardware52
- Banking & Financial Services43
What Employers Look For
The qualifications that appear most often in learning and development officer jobs.
- Bachelor's degree in human resources, education, organizational development, or a related field
- Experience designing and facilitating instructor-led and eLearning training programs
- Proficiency with learning management systems such as Cornerstone, Workday Learning, or similar platforms
- Familiarity with instructional design models including ADDIE or SAM
- Strong project management skills with the ability to manage multiple programs simultaneously
- CPTD or CPLP certification from ATD preferred for mid-level and senior roles
Tips for Your Learning and Development Officer Job Search
Align your resume to learning outcomes
Hiring managers for learning and development officer roles want to see measurable results, not just program names. Reframe every entry around learner performance gains, completion rates, or behavior changes you drove, not the tools or platforms you used to deliver training.
Lead with your instructional design philosophy
Many learning and development officer postings ask for a design philosophy or sample work upfront. Prepare a one-page philosophy statement and two to three portfolio samples showing needs analysis, design decisions, and evaluation results before you start applying.
Target postings by organizational maturity
A startup building its L&D function from scratch needs a different skill set than a Fortune 500 optimizing an existing program. Read the job description carefully for signals like 'build from scratch' or 'scale existing programs' and tailor your application to that specific stage.
Apply early to roles that fit
Migrate Mate lists learning and development officer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a performance consulting case study
Interviewers increasingly ask learning and development officer candidates to walk through how they diagnosed a performance gap and chose a solution. Practice narrating a real example using a gap analysis framework, connecting the business problem to the learning intervention you designed.
Negotiate scope before negotiating anything else
Before accepting an offer, clarify whether the role owns needs analysis, vendor relationships, and evaluation, or only delivers pre-scoped content. Scope determines your actual influence and career trajectory more than title or team size, so get it in writing during the offer stage.
Learning and Development Officer Jobs: Frequently Asked Questions
Which companies are hiring the most learning and development officers?
The companies hiring the most learning and development officers right now include Apple, TikTok, and Meta, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of November 2026. Healthcare networks, large financial institutions, and enterprise technology firms consistently maintain the highest volume of active openings.
How many learning and development officer jobs are remote?
About 58% of learning and development officer openings are fully remote or hybrid as of November 2026, reflecting strong employer flexibility for this role. Instructional design, eLearning development, and program management sub-functions tend to have the highest remote availability, while roles requiring in-person facilitation or new-hire onboarding are more likely to require on-site presence.
How do you become a learning and development officer?
Most learning and development officers start by earning a degree in human resources, education, or organizational development, then build hands-on experience facilitating training or designing curriculum in an adjacent role such as HR coordinator or training specialist. Earning an ATD certification like the CPTD strengthens your candidacy, and building a portfolio of instructional design samples is essential before applying to officer-level positions.
Can you get a learning and development officer job with little experience?
Yes, some entry-level learning and development officer roles are open to candidates with limited formal experience, particularly in organizations building their L&D function for the first time. Volunteering to design onboarding materials, facilitate internal workshops, or manage a learning management system in a current role, even informally, creates the portfolio evidence that compensates for a shorter work history.
What does the learning and development officer interview process look like?
The interview process for a learning and development officer role typically includes an initial screening call with HR, a competency-based panel interview focused on instructional design decisions and stakeholder management, and a practical exercise such as a training needs analysis presentation or a live facilitation sample. Final-round interviews often include a conversation with a business unit leader to assess strategic alignment.
Where can I find and apply to learning and development officer jobs?
You can find and apply to learning and development officer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your experience level and specialization, then apply directly to each one that fits.
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