Machine Learning Scientist Jobs
Machine Learning Scientist jobs are open across technology, healthcare, finance, and defense, from new-grad to principal and staff scientist levels, with common specializations in natural language processing, computer vision, and reinforcement learning. Find a role that fits from the openings below and apply directly.
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Showing 5 of 204+ Machine Learning Scientist jobs
At JPMorgan Chase, AI and technology promote our global operations with unmatched scale and speed. We invest over $18 billion annually in innovation, data leverage, and security to shape the future for our clients, communities, and employees. The Chief Data & Analytics Office (CDAO) accelerates our data and analytics journey, with the Machine Learning Center of Excellence (MLCOE) creating and deploying solutions for complex business challenges. By ensuring data quality and leveraging insights, the CDAO supports our commercial goals, enhancing productivity and risk management through AI and machine learning. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.
As a Machine Learning Scientist – Natural Language Processing (NLP) - Senior Associate, you will own the full lifecycle of developing and deploying machine learning solutions, from ideation to production. Acting as a leading voice within JPMC on all things Generative AI (GenAI), you will partner closely with all lines of business to innovate new solutions that drive transformational change for the bank. You will actively participate in our knowledge sharing community, representing your work inside and outside of the firm at leading industry conferences amongst peers and leaders in the space. We seek someone who excels in a highly collaborative, fast-paced environment, and holds a strong passion for machine learning to make a significant impact at a leading global financial institution.
Job responsibilities
- Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
- Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
- Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
- Lead firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
Required qualifications, capabilities, and skills
- PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, OR an MS with at least 2 years of industry or research experience in the field
- Solid background in Generative AI (GenAI) and hands-on experience and solid understanding of machine learning and deep learning methods and toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
- Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
Preferred qualifications, capabilities, and skills
- Strong background in Mathematics and Statistics; Familiarity with the financial services industries and continuous integration models and unit test development
- Knowledge in search/ranking or Meta Learning
- Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large-scale distributed environment, and ability to develop and debug production-quality code
- Published research in areas of Machine Learning or Deep Learning at a major conference or journal
#MLCOE_jobs
#CDAO_CAO_jobs
ABOUT USWe offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
At JPMorgan Chase, AI and technology promote our global operations with unmatched scale and speed. We invest over $18 billion annually in innovation, data leverage, and security to shape the future for our clients, communities, and employees. The Chief Data & Analytics Office (CDAO) accelerates our data and analytics journey, with the Machine Learning Center of Excellence (MLCOE) creating and deploying solutions for complex business challenges. By ensuring data quality and leveraging insights, the CDAO supports our commercial goals, enhancing productivity and risk management through AI and machine learning. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.
As a Machine Learning Scientist – Natural Language Processing (NLP) - Senior Associate, you will own the full lifecycle of developing and deploying machine learning solutions, from ideation to production. Acting as a leading voice within JPMC on all things Generative AI (GenAI), you will partner closely with all lines of business to innovate new solutions that drive transformational change for the bank. You will actively participate in our knowledge sharing community, representing your work inside and outside of the firm at leading industry conferences amongst peers and leaders in the space. We seek someone who excels in a highly collaborative, fast-paced environment, and holds a strong passion for machine learning to make a significant impact at a leading global financial institution.
Job responsibilities
- Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
- Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
- Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
- Lead firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
Required qualifications, capabilities, and skills
- PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, OR an MS with at least 2 years of industry or research experience in the field
- Solid background in Generative AI (GenAI) and hands-on experience and solid understanding of machine learning and deep learning methods and toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
- Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
Preferred qualifications, capabilities, and skills
- Strong background in Mathematics and Statistics; Familiarity with the financial services industries and continuous integration models and unit test development
- Knowledge in search/ranking or Meta Learning
- Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large-scale distributed environment, and ability to develop and debug production-quality code
- Published research in areas of Machine Learning or Deep Learning at a major conference or journal
#MLCOE_jobs
#CDAO_CAO_jobs
ABOUT USWe offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Machine Learning Scientist Jobs by Experience Level
Top Cities Hiring Machine Learning Scientists
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Find JobsMachine Learning Scientist Job Market
Who's Hiring
- SentiLink13
- Apple12
- Lila Sciences12
- Scale AI11
- TikTok9
Top Industries Hiring
- Technology & Software49
- Biotechnology & Pharmaceuticals17
- Electronics & Hardware11
- Artificial Intelligence9
- Banking & Financial Services7
What Employers Look For
The qualifications that appear most often in machine learning scientist jobs.
- PhD or MS in computer science, statistics, or a closely related quantitative field
- Proficiency in Python with deep experience in PyTorch or TensorFlow
- Experience designing, training, and evaluating large-scale machine learning models
- Familiarity with cloud ML infrastructure such as AWS SageMaker, GCP Vertex AI, or Azure ML
- Strong publication record or demonstrated applied research output
- Experience with distributed training, model optimization, or MLOps pipelines
Tips for Your Machine Learning Scientist Job Search
Tailor your resume to research depth
Hiring managers for machine learning scientist roles expect to see publications, preprints, or internal research artifacts. List your contributions explicitly, including whether you were lead author, and tie each project to a measurable outcome like latency reduction or model accuracy gain.
Apply early to roles that fit
Migrate Mate lists machine learning scientist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by research versus applied focus
Some machine learning scientist roles are primarily research-oriented with publish-or-present expectations, while others are production-focused. Read job descriptions for phrases like 'deploy at scale' or 'publish in top-tier venues' to identify which track fits your background before applying.
Prepare a take-home or live coding portfolio
Many machine learning scientist interviews include a system design or modeling exercise. Have at least one end-to-end project you can walk through live, covering data preprocessing decisions, architecture choices, and how you evaluated tradeoffs against simpler baselines.
Negotiate compute access alongside compensation
When you reach the offer stage, ask specifically about GPU cluster access, cloud compute budgets, and time allocated to exploratory research. These resources directly affect your ability to do the work and are negotiable at many organizations, especially in research-heavy teams.
Follow up with a specific technical observation
After an interview, reference a concrete detail from a technical discussion rather than sending a generic thank-you. Mentioning a specific modeling tradeoff you discussed shows genuine engagement and reinforces your fit for a role that demands scientific rigor.
Machine Learning Scientist Jobs: Frequently Asked Questions
Which companies are hiring the most machine learning scientists?
The companies hiring the most machine learning scientists right now include SentiLink, Apple, and Lila Sciences, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of September 2026. Demand is concentrated in technology, healthcare AI, and financial services.
How many machine learning scientist jobs are remote?
About 42% of machine learning scientist openings are fully remote or hybrid as of September 2026, making it one of the more location-flexible research roles. Sub-areas like natural language processing and computer vision research tend to have the highest share of remote positions, while roles tied to proprietary hardware or on-site data tend to require in-person work.
How do you become a machine learning scientist?
Most machine learning scientists build their foundation through a graduate degree in computer science, statistics, or applied mathematics, followed by research experience through internships, lab work, or industry projects. Developing a public portfolio of end-to-end projects, contributing to open-source machine learning libraries, and publishing or presenting findings in research communities helps demonstrate applied depth beyond coursework.
Can you get hired as a machine learning scientist without much experience?
Entry-level machine learning scientist roles do exist, but they typically require demonstrated research output rather than just coursework. Strong candidates with limited industry experience compensate by publishing preprints, contributing meaningfully to open-source projects, completing competitive research internships, or producing detailed public project write-ups that show end-to-end problem-solving at a research level.
What does the machine learning scientist interview process look like?
Machine learning scientist interviews typically include a resume and research background screen, followed by technical rounds covering machine learning theory, coding exercises in Python, and system design or modeling case studies. Many processes also include a research presentation where you walk through a past project in depth. Final rounds often involve meetings with cross-functional stakeholders or research leads assessing scientific communication and collaboration fit.
Where can I find and apply to machine learning scientist jobs?
You can find and apply to machine learning scientist jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your background and specialization, then apply directly to each listing that fits.
See All 204+ Machine Learning Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
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