Machine Learning Manager Jobs
Machine Learning Manager jobs are open across technology, healthcare, financial services, and e-commerce, from senior individual contributor to director level, with specializations in natural language processing, computer vision, and applied research. Find a role that fits from the openings below and apply directly.
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Showing 5 of 1,658+ Machine Learning Manager jobs
INTRODUCTION
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
ABOUT THE TEAM
We’re part of Plaid’s Data organization, building models that help millions of people better understand and grow their financial lives. We apply machine learning to high-impact product challenges, working across product areas to develop solutions that create meaningful customer value. We focus on credit, building models to the standards required in lending and supporting the next wave of cash-flow-based underwriting. We value technical expertise, creativity, user empathy, and teamwork, and we’re guided by Plaid’s principles of impact, growing together, openness and positivity, and inventing tomorrow.
ABOUT THE ROLE
As a Machine Learning Engineer on the Credit team, you’ll design, build, and deploy scalable machine learning solutions that support LendScore and the future of cash-flow-based underwriting. You’ll work across the full model lifecycle—from experimentation and offline training through production serving and monitoring—and partner with engineers and cross-functional teams to turn data and new modeling approaches into reliable systems.
YOUR ROLE AND RESPONSIBILITIES
- Develop and productionize AI and machine learning models, from offline training through online serving and ongoing monitoring.
- Experiment with modeling approaches and strategies for credit use cases, balancing model performance with the requirements of lending environments.
- Partner with engineering teams to ingest signals and build the systems needed to bring models into production.
- Contribute to both 0-to-1 problems and the scaling and improvement of established solutions.
- Collaborate with teams across Plaid to help define the machine learning roadmap.
- Dive into data and use evidence-based analysis to guide day-to-day decisions.
WHAT EXCITES YOU
- Building products that can empower millions of people through well-known and emerging fintech applications.
- Experimenting with modern machine learning techniques on meaningful credit and lending problems.
- Working across the full lifecycle of machine learning systems, from exploration to production and ongoing improvement.
- Taking on both greenfield challenges and opportunities to scale solutions that are already delivering value.
- Joining a high-ownership, bottom-up team where your work can shape the roadmap and drive business impact.
WHAT EXCITES US
- 2+ years of experience training and serving AI or machine learning models in a production environment.
- Experience in fintech lending and a strong understanding of how models are built and used in lending.
- Experience building or working with data-intensive backend applications in large, distributed systems.
- Ability to code and iterate independently using data infrastructure tools such as Python, Spark, Jupyter notebooks, and standard machine learning libraries.
- A track record of taking ownership and driving projects to business impact.
- Ability to work effectively with both technical and non-technical teams.
- Master’s degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field.
- Nice to have: Experience in data analytics or data engineering.
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws.
Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.
Please review our Candidate Privacy Notice here.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.
COMPENSATION RANGE
- Compensation Range: $211,680 - $272,160
INTRODUCTION
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
ABOUT THE TEAM
We’re part of Plaid’s Data organization, building models that help millions of people better understand and grow their financial lives. We apply machine learning to high-impact product challenges, working across product areas to develop solutions that create meaningful customer value. We focus on credit, building models to the standards required in lending and supporting the next wave of cash-flow-based underwriting. We value technical expertise, creativity, user empathy, and teamwork, and we’re guided by Plaid’s principles of impact, growing together, openness and positivity, and inventing tomorrow.
ABOUT THE ROLE
As a Machine Learning Engineer on the Credit team, you’ll design, build, and deploy scalable machine learning solutions that support LendScore and the future of cash-flow-based underwriting. You’ll work across the full model lifecycle—from experimentation and offline training through production serving and monitoring—and partner with engineers and cross-functional teams to turn data and new modeling approaches into reliable systems.
YOUR ROLE AND RESPONSIBILITIES
- Develop and productionize AI and machine learning models, from offline training through online serving and ongoing monitoring.
- Experiment with modeling approaches and strategies for credit use cases, balancing model performance with the requirements of lending environments.
- Partner with engineering teams to ingest signals and build the systems needed to bring models into production.
- Contribute to both 0-to-1 problems and the scaling and improvement of established solutions.
- Collaborate with teams across Plaid to help define the machine learning roadmap.
- Dive into data and use evidence-based analysis to guide day-to-day decisions.
WHAT EXCITES YOU
- Building products that can empower millions of people through well-known and emerging fintech applications.
- Experimenting with modern machine learning techniques on meaningful credit and lending problems.
- Working across the full lifecycle of machine learning systems, from exploration to production and ongoing improvement.
- Taking on both greenfield challenges and opportunities to scale solutions that are already delivering value.
- Joining a high-ownership, bottom-up team where your work can shape the roadmap and drive business impact.
WHAT EXCITES US
- 2+ years of experience training and serving AI or machine learning models in a production environment.
- Experience in fintech lending and a strong understanding of how models are built and used in lending.
- Experience building or working with data-intensive backend applications in large, distributed systems.
- Ability to code and iterate independently using data infrastructure tools such as Python, Spark, Jupyter notebooks, and standard machine learning libraries.
- A track record of taking ownership and driving projects to business impact.
- Ability to work effectively with both technical and non-technical teams.
- Master’s degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field.
- Nice to have: Experience in data analytics or data engineering.
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws.
Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.
Please review our Candidate Privacy Notice here.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.
COMPENSATION RANGE
- Compensation Range: $211,680 - $272,160
Machine Learning Manager Jobs by Experience Level
Top Cities Hiring Machine Learning Managers
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Find Machine Learning Manager JobsMachine Learning Manager Job Market
Who's Hiring
- TikTok88
- Meta61
- Uber46
- Lockheed Martin41
- Atlas Technologies36
Top Industries Hiring
- Technology & Software90
- Electronics & Hardware13
- Biotechnology & Pharmaceuticals12
- Education5
- Manufacturing5
What Employers Look For
The qualifications that appear most often in machine learning manager jobs.
- 5+ years of machine learning experience with at least 2 years managing or leading teams
- Proficiency in Python and frameworks such as PyTorch, TensorFlow, or JAX
- Experience taking machine learning models from prototype to production at scale
- Strong cross-functional collaboration skills with product, engineering, and data teams
- Familiarity with MLOps tooling including experiment tracking, model registries, and CI/CD pipelines
- Graduate degree in computer science, statistics, mathematics, or a closely related field
Tips for Your Machine Learning Manager Job Search
Quantify model impact on your resume
Machine learning manager resumes stall when they list tools instead of outcomes. Replace 'managed NLP models' with the latency reduction, accuracy lift, or revenue impact your team's models delivered. Hiring managers compare you on measurable results, not tech stacks.
Apply early to roles that fit
Migrate Mate lists machine learning manager openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter by research versus product focus
A machine learning manager role at a research lab expects publications and grant experience, while a product-focused company wants shipped models and cross-functional delivery. Read job descriptions for phrases like 'production systems' or 'state of the art' to target your applications correctly.
Prepare a technical leadership narrative
Interviews will probe how you balance coding depth with people management. Prepare two or three stories where you made a concrete architectural decision, explained the trade-offs to non-technical stakeholders, and coached an engineer through a technical challenge.
Negotiate using scope, not just title
Before accepting an offer, clarify team size, compute budget, and roadmap ownership. A machine learning manager with a three-person team and no GPU budget has a different career trajectory than one owning a ten-person org. Scope shapes your next move more than title does.
Follow up with a technical insight
After a final-round interview, send a follow-up that references a specific problem from the conversation and proposes a brief framing or approach. It demonstrates the research and systems thinking that separates machine learning manager candidates from individual contributors.
Machine Learning Manager Jobs: Frequently Asked Questions
Which companies are hiring the most machine learning managers?
The companies hiring the most machine learning managers right now include TikTok, Meta, and Uber, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of November 2026. Demand is concentrated in companies with large-scale data infrastructure and active model deployment programs.
How many machine learning manager jobs are remote?
About 71% of machine learning manager openings are fully remote or hybrid as of November 2026, making it one of the more flexible senior technical roles available. Applied research and platform infrastructure sub-areas tend to have the highest share of fully remote positions, while roles tied to on-site hardware or real-time systems more often require in-person presence.
How do you become a machine learning manager?
Start by building a strong record as a machine learning engineer or research scientist, then take on informal leadership by mentoring junior teammates and owning a project end to end. Transition into a formal lead or tech lead role to gain people management exposure. Demonstrate business impact through shipped models, then make the case for a manager title with evidence of team development and cross-functional delivery.
Can you get a machine learning manager job without direct management experience?
Yes, many companies hire senior machine learning engineers into their first manager role when those engineers have led projects, mentored colleagues, and collaborated across teams. Framing your resume around influence, decision-making, and team outcomes rather than individual model work is what moves your application from the individual contributor pile into manager consideration.
What does the machine learning manager interview process look like?
The process typically opens with a recruiter screen covering background and role fit, followed by a technical interview that tests machine learning fundamentals and system design for production ML pipelines. A separate round focuses on people management scenarios and cross-functional communication. Final rounds often include a presentation to leadership covering a past project, a proposed roadmap, or a take-home case study on a relevant modeling problem.
Where can I find and apply to machine learning manager jobs?
You can find and apply to machine learning manager jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background and experience level, then apply directly to each one that fits.
See All 1,658+ Machine Learning Manager Jobs
Find roles that match your experience and apply in just a few clicks.
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