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 1,025+ Machine Learning Scientist jobs
The Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Opportunity
We are seeking a highly motivated and collaborative Senior/Principal Machine Learning Scientist to join the Perturbation Biology group in the Department of AI for Biology & Translation (AIBT) in Genentech Research and Early Development (gRED). The successful candidate will develop the next generation of machine learning models to derive actionable insights from large-scale high-content perturbation experiments for target and drug discovery. This role requires a deep understanding of machine learning applied to sequencing-based perturbation data, a passion for innovation and inter-disciplinary research, and a commitment to improving healthcare outcomes through cutting-edge technology. We are looking for exceptional researchers with a proven ability to develop and implement research ideas. The candidate is expected to lead high profile projects in collaboration with our therapeutic area leads, and to routinely publish work in top-tier machine learning and scientific venues.
In this role, you will:
- Design and apply predictive machine learning algorithms for lab-in-the-loop perturbation screens for drug and target identification.
- Work on and integrate a variety of different data modalities such as molecular structures, omics data, images, and text.
- Collaborate with interdisciplinary and cross-functional teams including biologists, chemists, data scientists, and other stakeholders.
- Build and scale machine learning techniques to massive datasets and aid in the deployment of novel machine learning algorithms.
- Publish in top-tier machine learning venues and/or scientific journals, present results at internal and external scientific venues, conferences, and workshops.
Who you are
-
Educational Background: PhD degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics) or in the physical or life sciences (e.g., Chemistry, Biology) with a strong quantitative focus
-
Experience:
-
Senior ML Scientist 0-2 years of experience post PhD, Principal ML Scientist 2-7 years of experience post PhD
- Proven track record of developing and applying advanced machine learning models in a research or industry setting.
-
Demonstrated interest in problems across biology and chemistry as applied to the discovery and development of treatments for disease.
-
Technical Skills:
-
Proficiency in scientific programming in Python.
- Extensive experience with Machine Learning frameworks and libraries (e.g., PyTorch, JAX, Tensorflow).
-
Strong background in statistics, probabilistic modeling and data analysis.
-
Soft Skills: Excellent communication, collaboration, and problem-solving skills.
-
Publications: Strong publication record and experience contributing to research communities, including conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc.
Preferred
-
Practical experience in one or more of the following areas:
-
Predictive modeling of perturbation datasets to drive experimental design
- Predictive modeling and/or generative modeling on molecules and other chemistry applications
- Multimodal data integration, in particular between multiple measurement modalities and/or clinical patient data
Relocation benefits are NOT available for this job posting.
The expected salary range for this position, based on the location of California, is $147,800 - 274,400 for the Senior ML Scientist, and $172,400 - 320,200 for the Principal ML Scientist. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
JOB FACTS
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Job Sub Category: Research Biology
-
Schedule: Full time
-
Job Type: Regular
-
Posted Date: Jun 17th 2026
-
Job ID: 202606-114787
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
The Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Opportunity
We are seeking a highly motivated and collaborative Senior/Principal Machine Learning Scientist to join the Perturbation Biology group in the Department of AI for Biology & Translation (AIBT) in Genentech Research and Early Development (gRED). The successful candidate will develop the next generation of machine learning models to derive actionable insights from large-scale high-content perturbation experiments for target and drug discovery. This role requires a deep understanding of machine learning applied to sequencing-based perturbation data, a passion for innovation and inter-disciplinary research, and a commitment to improving healthcare outcomes through cutting-edge technology. We are looking for exceptional researchers with a proven ability to develop and implement research ideas. The candidate is expected to lead high profile projects in collaboration with our therapeutic area leads, and to routinely publish work in top-tier machine learning and scientific venues.
In this role, you will:
- Design and apply predictive machine learning algorithms for lab-in-the-loop perturbation screens for drug and target identification.
- Work on and integrate a variety of different data modalities such as molecular structures, omics data, images, and text.
- Collaborate with interdisciplinary and cross-functional teams including biologists, chemists, data scientists, and other stakeholders.
- Build and scale machine learning techniques to massive datasets and aid in the deployment of novel machine learning algorithms.
- Publish in top-tier machine learning venues and/or scientific journals, present results at internal and external scientific venues, conferences, and workshops.
Who you are
-
Educational Background: PhD degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics) or in the physical or life sciences (e.g., Chemistry, Biology) with a strong quantitative focus
-
Experience:
-
Senior ML Scientist 0-2 years of experience post PhD, Principal ML Scientist 2-7 years of experience post PhD
- Proven track record of developing and applying advanced machine learning models in a research or industry setting.
-
Demonstrated interest in problems across biology and chemistry as applied to the discovery and development of treatments for disease.
-
Technical Skills:
-
Proficiency in scientific programming in Python.
- Extensive experience with Machine Learning frameworks and libraries (e.g., PyTorch, JAX, Tensorflow).
-
Strong background in statistics, probabilistic modeling and data analysis.
-
Soft Skills: Excellent communication, collaboration, and problem-solving skills.
-
Publications: Strong publication record and experience contributing to research communities, including conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc.
Preferred
-
Practical experience in one or more of the following areas:
-
Predictive modeling of perturbation datasets to drive experimental design
- Predictive modeling and/or generative modeling on molecules and other chemistry applications
- Multimodal data integration, in particular between multiple measurement modalities and/or clinical patient data
Relocation benefits are NOT available for this job posting.
The expected salary range for this position, based on the location of California, is $147,800 - 274,400 for the Senior ML Scientist, and $172,400 - 320,200 for the Principal ML Scientist. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
JOB FACTS
-
Job Sub Category: Research Biology
-
Schedule: Full time
-
Job Type: Regular
-
Posted Date: Jun 17th 2026
-
Job ID: 202606-114787
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
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Find JobsMachine Learning Scientist Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Amazon156
- TikTok42
- Apple36
- Walmart28
- Capital One27
Top Industries Hiring
- Technology & Software362
- Consulting & Professional Services65
- Electronics & Hardware61
- Banking & Financial Services52
- Retail51
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 Amazon, TikTok, and Apple, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of June 2026. Demand is concentrated in technology, healthcare AI, and financial services.
How many machine learning scientist jobs are remote?
About 26% of machine learning scientist openings are fully remote or hybrid as of June 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 1,025+ Machine Learning Scientist Jobs
Jump back to the full list of openings and apply to any machine learning scientist role that fits.
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