Remote Machine Learning Scientist Jobs
Remote Machine Learning Scientist jobs are open across the U.S. at remote-first firms, distributed research teams, and technology-driven companies in sectors like software, healthcare, and finance. Employers hiring remote machine learning scientists right now include Rad AI, NEOTAX, and Target. Scan the live roles below and apply to whichever ones fit.
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Showing 4 of 14+ Remote Machine Learning Scientist jobs
Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.
JOIN TARGET AS A LEAD DATA SCIENTIST – RECOMMENDATIONS (RecSys)
About Us:
Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.
A role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Every scientist on Target’s Data Sciences team can expect to do modeling and data science, develop software with highly performant code, elevate Target’s culture, and apply retail domain knowledge.
As a Lead Data Scientist - Recommendations, you will provide technical leadership for the machine learning systems that power Target's digital recommendations and personalization experiences. Working closely with data scientists, engineers, product managers, and business stakeholders, you will identify opportunities to improve guest experiences through recommendation, retrieval, ranking, and personalization solutions at a massive scale.
You will lead the design, development, evaluation, and deployment of machine learning models that influence how millions of guests discover products across Target's digital experiences. Leveraging expertise in machine learning, deep learning, experimentation, and optimization, you will translate ambiguous business challenges into scalable algorithmic solutions that drive measurable guest and business impact. You will be responsible for driving projects from initial problem definition through production deployment and measurement, balancing innovation with operational excellence and long-term maintainability. You will help shape the technical direction of Target's recommendation capabilities, establishing best practices for model development, evaluation, and measurement while influencing decisions across product, engineering, and data science teams.
Beyond delivering solutions, you will mentor and develop other scientists, help raise the technical bar across the organization, and contribute to the growth of Target's data science community through collaboration, thought leadership, and the adoption of emerging machine learning techniques and technologies.
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About you:
- PhD or MS in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research, or a related quantitative field with 2+ years of industry experience
- 5+ years of experience developing machine learning solutions scaling recommendation, personalization, ranking, retrieval, or search machine learning systems
- Experience with reinforcement learning and/or contextual bandit design, implementation, and evaluation
- Experience leading the development, evaluation, and deployment of machine learning solutions and partnering with engineering teams to deliver scalable production systems
- Strong programming skills in Python and SQL; experience with deep learning frameworks such as PyTorch or JAX
- Experience working with large-scale data processing and analytics platforms such as Spark or equivalent
- Deep understanding of machine learning, deep learning, optimization, statistics, probability, and experimental design
- Experience designing, analyzing, and interpreting online experiments and using results to inform product and business decisions
- Demonstrated ability to translate ambiguous business challenges into scalable machine learning solutions
- Demonstrated ability to influence technical direction and drive alignment across product, engineering, and business stakeholders
- Experience leveraging modern AI and generative AI tools to accelerate development, experimentation, and model delivery
- Excellent communication skills with the ability to clearly communicate complex technical concepts to both technical and non-technical audiences
- Strong software engineering fundamentals, including testing, code reviews, documentation, and maintainable system design
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_EAmericans with Disabilities Act (ADA)
In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.
Application deadline is : 10/29/2026Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.
JOIN TARGET AS A LEAD DATA SCIENTIST – RECOMMENDATIONS (RecSys)
About Us:
Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.
A role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Every scientist on Target’s Data Sciences team can expect to do modeling and data science, develop software with highly performant code, elevate Target’s culture, and apply retail domain knowledge.
As a Lead Data Scientist - Recommendations, you will provide technical leadership for the machine learning systems that power Target's digital recommendations and personalization experiences. Working closely with data scientists, engineers, product managers, and business stakeholders, you will identify opportunities to improve guest experiences through recommendation, retrieval, ranking, and personalization solutions at a massive scale.
You will lead the design, development, evaluation, and deployment of machine learning models that influence how millions of guests discover products across Target's digital experiences. Leveraging expertise in machine learning, deep learning, experimentation, and optimization, you will translate ambiguous business challenges into scalable algorithmic solutions that drive measurable guest and business impact. You will be responsible for driving projects from initial problem definition through production deployment and measurement, balancing innovation with operational excellence and long-term maintainability. You will help shape the technical direction of Target's recommendation capabilities, establishing best practices for model development, evaluation, and measurement while influencing decisions across product, engineering, and data science teams.
Beyond delivering solutions, you will mentor and develop other scientists, help raise the technical bar across the organization, and contribute to the growth of Target's data science community through collaboration, thought leadership, and the adoption of emerging machine learning techniques and technologies.
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About you:
- PhD or MS in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research, or a related quantitative field with 2+ years of industry experience
- 5+ years of experience developing machine learning solutions scaling recommendation, personalization, ranking, retrieval, or search machine learning systems
- Experience with reinforcement learning and/or contextual bandit design, implementation, and evaluation
- Experience leading the development, evaluation, and deployment of machine learning solutions and partnering with engineering teams to deliver scalable production systems
- Strong programming skills in Python and SQL; experience with deep learning frameworks such as PyTorch or JAX
- Experience working with large-scale data processing and analytics platforms such as Spark or equivalent
- Deep understanding of machine learning, deep learning, optimization, statistics, probability, and experimental design
- Experience designing, analyzing, and interpreting online experiments and using results to inform product and business decisions
- Demonstrated ability to translate ambiguous business challenges into scalable machine learning solutions
- Demonstrated ability to influence technical direction and drive alignment across product, engineering, and business stakeholders
- Experience leveraging modern AI and generative AI tools to accelerate development, experimentation, and model delivery
- Excellent communication skills with the ability to clearly communicate complex technical concepts to both technical and non-technical audiences
- Strong software engineering fundamentals, including testing, code reviews, documentation, and maintainable system design
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_EAmericans with Disabilities Act (ADA)
In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.
Application deadline is : 10/29/2026See All 14 Remote Machine Learning Scientist Jobs
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Find JobsRemote Machine Learning Scientist Job Market
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Accounting & Auditing
What Employers Look For
The qualifications that appear most often in remote 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 Remote Machine Learning Scientist Job Search
Apply early to remote roles that fit
Migrate Mate lists remote machine learning scientist openings from across the U.S. in one place, so you can find roles that match your skills and apply directly. Remote postings fill fast, so checking regularly and applying as soon as a strong fit appears gives you a real advantage.
Build a portfolio of reproducible experiments
Remote employers can't watch you work, so your code and notebooks do the talking. Host documented, reproducible experiments on GitHub that show your modeling decisions, not just final results. Clear commit histories and README files signal you can collaborate asynchronously on a distributed team.
Highlight async communication in your materials
Remote machine learning scientist roles require written communication that keeps distributed teammates aligned without meetings. Mention specific tools you've used, like GitHub pull requests, Confluence, or Weights and Biases experiment logs, and describe how your documentation practices kept cross-functional teams informed on model development progress.
Target remote-first companies in your research
Companies built as remote-first from the start have the infrastructure and culture to support distributed machine learning scientists effectively. Look for firms with fully distributed engineering and research teams, because those organizations hire remote scientists regularly and have onboarding processes designed for async work.
Remote Machine Learning Scientist Jobs: Frequently Asked Questions
How do I get a remote machine learning scientist job?
Focus on companies that operate distributed research teams, because those employers are already set up to manage remote scientists and actively hire them. Remote hiring managers screen hard for self-direction, clear written communication, and the ability to document experiments so teammates in different time zones can follow your reasoning. A public portfolio of reproducible work, strong Python and ML framework proficiency, and experience collaborating through async tools like GitHub and Confluence give candidates a clear edge.
Which companies hire remote machine learning scientists?
Companies hiring remote machine learning scientists right now include Rad AI, NEOTAX, and Target, based on current remote listings on Migrate Mate as of September 2026. Remote-first technology firms and distributed teams in software, healthcare, and financial services are among the most consistent hirers of machine learning scientists in fully remote roles.
Can you get a remote machine learning scientist job with no experience?
Yes, but remote entry-level machine learning scientist roles are harder to land because employers expect you to work independently from day one with minimal hand-holding. Smaller remote-first startups and research-oriented companies are more open to early-career candidates who can show original project work, published or open-source contributions, and strong written documentation skills that signal you'll function well on a distributed team.
Do you need a degree for remote machine learning scientist jobs?
Usually, but not always. Most remote machine learning scientist postings list a graduate degree as a preference, but remote employers increasingly weigh demonstrated skills, reproducible research, and real-world results alongside formal credentials. A strong portfolio of model development work, peer-reviewed contributions, or verifiable production deployments can offset the absence of an advanced degree for the right role.
Which industries hire the most remote machine learning scientists?
The sectors hiring the most remote machine learning scientists are Biotechnology & Pharmaceuticals and Accounting & Auditing, based on current remote listings on Migrate Mate as of September 2026. Those industries rely on distributed research and engineering teams that are structured to support scientists working fully remotely from the start.
See All 14 Remote Machine Learning Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
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