Machine Learning Specialist Jobs
Machine Learning Specialist jobs are open from new-grad to principal across technology, healthcare, finance, and retail, with specializations in natural language processing, computer vision, and recommendation systems. See the openings below and apply to the ones that match your experience.
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Showing 5 of 1,960+ Machine Learning Specialist jobs
Software EngineeringMountain View, CA (HQ), San Francisco, CA
About the team:
Tapestry is X’s moonshot for the electric grid. We’re transforming how the world makes, moves and uses electricity, using AI to reshape energy on a global scale.
We’re looking for curious minds who want to be a part of this extraordinary moment in energy. You would be joining a multidisciplinary team from a wide variety of experiences and backgrounds—from ML/AI and power systems experts to software engineers and energy entrepreneurs– working together to realize Tapestry’s mission to make the grid visible so that everyone, everywhere can access reliable, abundant, and clean energy.
Tapestry is incubating at X, Alphabet’s Moonshot Factory—the birthplace of breakthrough technologies like Waymo, Android and Google Brain. At Tapestry, you’ll have the chance to be part of a rapidly growing team that has the agility and impact of an early stage company with the resources and technical excellence of Alphabet. If developing multimodal AI solutions gets you up in the morning and load growth challenges keep you up at night, we'd love to meet you.
Learn more about our team and our mission here.
About the role:
We're looking for a Senior Research Engineer to join the Machine Learning team. In this role, you will be responsible for developing and deploying state of the art machine learning models to solve complex challenges that face today’s electric grid. You’ll have the opportunity to lead model building and development across diverse ML domains such as computer vision, natural language understanding, representation learning and agentic AI. In this role, you will be responsible for end to end ML model training and deployment, working with and mentoring junior machine learning engineers, helping lead cross-functional collaborations and build the state of the art machine learning models to help power the grid of tomorrow.
How you will make 10x impact:
- Design, train, and deploy machine learning models in production environments.
- Lead the end to end development of ML systems for one or more of multimodal machine learning, agentic systems and LLMs, representation learning
- Actively collaborate with leaders in product, engineering, and data science teams to address key business problems
- Mentor junior engineers and scientists and contribute to the team’s technical growth.
- Stay abreast of the latest advancements in machine learning
What you should have:
- Master’s Degree/Bachelor's Degree in Machine Learning, Computer Science, Statistics or equivalent practical experience.
- 6+ years of professional experience in machine learning model development and engineering.
- Strong programming skills in Python and experience with ML frameworks like PyTorch or TensorFlow.
- Experience with building and deploying ML systems at scale, and a proven ability to perform applied ML research and develop the state of the art
- Proven ability to work on cross-functional projects and deliver results in a fast-paced, collaborative environment
It’d be great if you also had these:
- PhD in Machine Learning, Computer Science, Statistics, or a related field
- Experience with cloud platforms such as AWS, GCP, or Azure.
- Familiarity with MLOps practices and tools.
- A strong portfolio of projects demonstrating expertise in multiple ML domai
Our values
- Take charge: We take initiative and own outcomes that move the mission forward.
- Transform with purpose: We build solutions that solve real problems and create meaningful impact.
- Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
- Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
- Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.
What we offer
A culture that supports growth, ownership, and meaningful impact, along with:
- Competitive salary and equity
- Medical, dental, and vision coverage
- Generous PTO and flexible hybrid work model
- 401(k) with employer contribution
- Professional development
- The ability to work on important real-world problems within an Alphabet-backed environment
The US base salary range for this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
.
An Equal Opportunity Workplace
At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you have a disability or special need that requires accommodation, please contact us at x-accommodation-request@x.team.
Software EngineeringMountain View, CA (HQ), San Francisco, CA
About the team:
Tapestry is X’s moonshot for the electric grid. We’re transforming how the world makes, moves and uses electricity, using AI to reshape energy on a global scale.
We’re looking for curious minds who want to be a part of this extraordinary moment in energy. You would be joining a multidisciplinary team from a wide variety of experiences and backgrounds—from ML/AI and power systems experts to software engineers and energy entrepreneurs– working together to realize Tapestry’s mission to make the grid visible so that everyone, everywhere can access reliable, abundant, and clean energy.
Tapestry is incubating at X, Alphabet’s Moonshot Factory—the birthplace of breakthrough technologies like Waymo, Android and Google Brain. At Tapestry, you’ll have the chance to be part of a rapidly growing team that has the agility and impact of an early stage company with the resources and technical excellence of Alphabet. If developing multimodal AI solutions gets you up in the morning and load growth challenges keep you up at night, we'd love to meet you.
Learn more about our team and our mission here.
About the role:
We're looking for a Senior Research Engineer to join the Machine Learning team. In this role, you will be responsible for developing and deploying state of the art machine learning models to solve complex challenges that face today’s electric grid. You’ll have the opportunity to lead model building and development across diverse ML domains such as computer vision, natural language understanding, representation learning and agentic AI. In this role, you will be responsible for end to end ML model training and deployment, working with and mentoring junior machine learning engineers, helping lead cross-functional collaborations and build the state of the art machine learning models to help power the grid of tomorrow.
How you will make 10x impact:
- Design, train, and deploy machine learning models in production environments.
- Lead the end to end development of ML systems for one or more of multimodal machine learning, agentic systems and LLMs, representation learning
- Actively collaborate with leaders in product, engineering, and data science teams to address key business problems
- Mentor junior engineers and scientists and contribute to the team’s technical growth.
- Stay abreast of the latest advancements in machine learning
What you should have:
- Master’s Degree/Bachelor's Degree in Machine Learning, Computer Science, Statistics or equivalent practical experience.
- 6+ years of professional experience in machine learning model development and engineering.
- Strong programming skills in Python and experience with ML frameworks like PyTorch or TensorFlow.
- Experience with building and deploying ML systems at scale, and a proven ability to perform applied ML research and develop the state of the art
- Proven ability to work on cross-functional projects and deliver results in a fast-paced, collaborative environment
It’d be great if you also had these:
- PhD in Machine Learning, Computer Science, Statistics, or a related field
- Experience with cloud platforms such as AWS, GCP, or Azure.
- Familiarity with MLOps practices and tools.
- A strong portfolio of projects demonstrating expertise in multiple ML domai
Our values
- Take charge: We take initiative and own outcomes that move the mission forward.
- Transform with purpose: We build solutions that solve real problems and create meaningful impact.
- Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
- Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
- Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.
What we offer
A culture that supports growth, ownership, and meaningful impact, along with:
- Competitive salary and equity
- Medical, dental, and vision coverage
- Generous PTO and flexible hybrid work model
- 401(k) with employer contribution
- Professional development
- The ability to work on important real-world problems within an Alphabet-backed environment
The US base salary range for this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
.
An Equal Opportunity Workplace
At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you have a disability or special need that requires accommodation, please contact us at x-accommodation-request@x.team.
Machine Learning Specialist Jobs by Experience Level
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Find JobsMachine Learning Specialist Job Market
Who's Hiring
- Apple196
- TikTok122
- Meta47
- Pinterest39
- Uber37
Top Industries Hiring
- Technology & Software308
- Artificial Intelligence65
- Electronics & Hardware45
- Social Media33
- Automotive27
What Employers Look For
The qualifications that appear most often in machine learning specialist jobs.
- Proficiency in Python and at least one deep learning framework such as PyTorch or TensorFlow
- Experience building and deploying end-to-end machine learning pipelines in production environments
- Strong foundation in statistics, probability, and linear algebra applied to modeling problems
- Familiarity with cloud ML platforms such as AWS SageMaker, Google Vertex AI, or Azure ML
- Experience with data preprocessing, feature engineering, and working with large-scale datasets
- Bachelor's or master's degree in computer science, statistics, mathematics, or a related technical field
Tips for Your Machine Learning Specialist Job Search
Tailor your resume to each stack
Machine learning postings vary widely by framework. Reorder your skills section so the specific tools in the job description, whether PyTorch, TensorFlow, or scikit-learn, appear near the top. Generic ML resumes get filtered out before a human ever reads them.
Quantify model impact, not just accuracy
Hiring managers care more about downstream business outcomes than benchmark scores. Replace accuracy metrics with what the model actually changed: latency reduced, revenue influenced, or manual review hours eliminated. That framing makes your work legible to non-technical interviewers too.
Apply early to roles that fit
Migrate Mate lists machine learning specialist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter postings by deployment context
A role shipping models to production via APIs is a very different job from one doing offline batch scoring. Read the systems section of each posting carefully and prioritize openings where the deployment environment matches your strongest experience.
Prepare a system design answer for ML
Most machine learning specialist loops include a design round where you architect an end-to-end pipeline from data ingestion through serving. Practice walking through feature engineering decisions, training infrastructure, and monitoring out loud before your first technical screen.
Negotiate with competing offer timelines
If you have more than one process running simultaneously, tell each recruiter you have an exploding offer and ask for a decision timeline. Machine learning roles often have flexible start dates, which gives you real leverage to align timelines rather than lose an offer you want.
Machine Learning Specialist Jobs: Frequently Asked Questions
Which companies are hiring the most machine learning specialists?
Apple, TikTok, and Meta are hiring the most machine learning specialists right now, with openings concentrated in California, Washington, and New York, based on current listings on Migrate Mate as of November 2026. Demand is especially high at companies scaling recommendation systems, fraud detection, and large language model applications.
How many machine learning specialist jobs are remote?
About 52% of machine learning specialist openings are fully remote or hybrid as of November 2026, reflecting strong employer flexibility in this role. Research, applied science, and NLP-focused positions tend to offer the highest share of remote arrangements, while roles tied to on-premises infrastructure or regulated data environments are more likely to require on-site presence.
How do you become a machine learning specialist?
Start by building a solid foundation in Python, linear algebra, and probability, then work through core ML concepts using hands-on projects. Develop practical experience with real datasets on platforms like Kaggle or through personal projects, build a portfolio demonstrating end-to-end pipelines, and move toward production deployment skills. A graduate degree accelerates entry into research-heavy roles, but strong project work can substitute for it in applied positions.
How do you get hired as a machine learning specialist with little experience?
Focus on a narrow specialization, such as NLP or computer vision, rather than presenting yourself as a generalist. Build two or three portfolio projects that demonstrate you can take a problem from raw data to a deployed or evaluable model. Contributing to open-source ML projects, publishing reproducible notebooks, and targeting smaller companies or startups with less competitive pipelines all improve your odds before you have years of full-time experience.
What does the machine learning specialist interview process look like?
Most processes run three to five rounds. An initial recruiter screen is followed by a technical phone interview covering coding and ML fundamentals. From there, candidates typically face a take-home or live coding exercise, an ML system design round where you architect a full pipeline, and a final loop with cross-functional stakeholders. Research and scientist-track roles often add a presentation of past work or a paper discussion.
Where can I find and apply to machine learning specialist jobs?
You can find and apply to machine learning specialist 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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