Remote Staff ML Engineer Jobs
Remote Staff ML Engineer jobs are in active demand across the U.S., with remote-first firms and distributed engineering teams hiring for senior individual contributor roles in sectors like enterprise software, fintech, and AI-native startups. Employers posting remote openings right now include Airbnb, reddit, and Payabli. See the openings below and apply to the ones that match your experience.
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Showing 5 of 27+ Remote Staff ML Engineer jobs
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
At Thermo Fisher Scientific, our Finance teams play a critical role in enabling informed, strategic decision-making that advances our Mission to enable our customers to make the world healthier, cleaner, and safer. Across FP&A, Tax, Treasury, Financial Reporting, Audit, Investor Relations, Strategy & Corporate Development, and Accounting, our global Finance organization provides diverse opportunities to shape business outcomes, drive innovation, and build meaningful career experiences.
We have a new opening within the Clinical Research Group (CRG) of Thermo Fisher for a Senior Staff AI/ML Solutions Engineer to support the Finance organization and serve as the hands-on technical lead for AI initiatives that improve finance business processes, decision-making, and productivity. You will translate business needs into practical AI solutions and lead their technical delivery from discovery and architecture through development, evaluation, deployment, and ongoing improvement.
This is a senior individual contributor role with responsibility for technical direction and project outcomes. You will collaborate across business and technology teams and provide technical guidance and mentoring to junior colleagues. People management may be included as business needs evolve, while hands-on technical leadership remains the primary responsibility.
This is a band 8 Remote position for qualified candidates in the US (EST or CST preference).
What you’ll do:
- Lead the technical delivery of AI projects, defining solution architecture, implementation plans, dependencies, and acceptance criteria.
- Partner with finance and other business stakeholders to identify valuable AI use cases, assess feasibility, and establish measurable outcomes.
- Design, build, and integrate AI applications using generative AI, machine learning, enterprise data, and workflow automation as appropriate to the business problem.
- Develop prototypes and production solutions, selecting technologies based on accuracy, reliability, security, scalability, performance, and cost.
- Establish evaluation approaches for AI outputs, including quality, robustness, and appropriate human review.
- Design and implement the data pipelines, APIs, and enterprise integrations needed to support AI solutions.
- Collaborate with IT, architecture, cybersecurity, privacy, and data governance teams to meet applicable requirements throughout development and deployment.
- Apply sound software engineering practices, including version control, code review, testing, documentation, and automated deployment.
- Define monitoring, support, and operational handoff requirements; investigate issues and improve deployed solutions.
- Communicate technical recommendations, tradeoffs, project risks, and results to technical and business audiences.
- Mentor junior data scientists and engineers through design reviews, code reviews, and collaborative problem-solving.
What you’ll need:
- Advanced degree and 6 years of computer science, data science, engineering, or a related technical field and AI experience, or Bachelor’s degree and 8 years of computer science, data science, engineering, or a related technical field and AI experience.
- Demonstrated experience serving as the technical lead for AI or advanced analytics projects, including delivery into production.
- Strong hands-on proficiency in Python and SQL, with experience building maintainable applications and data integrations.
- Practical experience developing generative AI solutions using platforms such as Azure OpenAI or Amazon Bedrock.
- Experience integrating AI models with enterprise data and applications, including retrieval-augmented generation, APIs, and workflow orchestration.
- Ability to evaluate AI solution quality and explain limitations, technical tradeoffs, and deployment considerations.
- Experience with cloud services and data platforms such as AWS, Azure, Snowflake, or Databricks.
- Working knowledge of data architecture, ETL/ELT processes, data quality, and access controls.
- Experience using version control, testing, CI/CD, and collaborative development tools.
- Strong communication skills and the ability to translate business needs into technical requirements and delivery plans.
- Demonstrated ability to guide technical contributors and coordinate delivery across functions
Preferred Qualifications:
- Experience applying AI to processes, analytics, or enterprise productivity.
- Experience with distributed data processing technologies such as PySpark, Apache Spark, and Delta Lake.
- Experience designing and implementing enterprise data models and semantic layers that support consistent business definitions, analytics, and AI applications
- Experience with predictive modeling and statistical analysis
- Experience using Azure DevOps or JIRA within Agile delivery teams.
At Thermo Fisher Scientific, we are committed to fostering a healthy and harmonious workplace for our employees. We understand the importance of creating an environment that allows individuals to excel. Please see below for the required qualifications for this position, which also includes the possibility of equivalent experience:
- Able to communicate, receive, and understand information and ideas with diverse groups of people in a comprehensible and reasonable manner.
- Able to work upright and stationary for typical working hours.
- Ability to use and learn standard office equipment and technology with proficiency.
- Able to perform successfully under pressure while prioritizing and handling multiple projects or activities.
- May require as-needed travel (0-20%).
Location: EST or CST remote US. Relocation assistance is NOT provided.
- Must be legally authorized to work in the United States without sponsorship.
- Must be able to pass a comprehensive background check, which includes a drug screening.
The annual salary range estimated for this position in North Carolina is $138,000 - $208,000 USD. This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy.
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
At Thermo Fisher Scientific, our Finance teams play a critical role in enabling informed, strategic decision-making that advances our Mission to enable our customers to make the world healthier, cleaner, and safer. Across FP&A, Tax, Treasury, Financial Reporting, Audit, Investor Relations, Strategy & Corporate Development, and Accounting, our global Finance organization provides diverse opportunities to shape business outcomes, drive innovation, and build meaningful career experiences.
We have a new opening within the Clinical Research Group (CRG) of Thermo Fisher for a Senior Staff AI/ML Solutions Engineer to support the Finance organization and serve as the hands-on technical lead for AI initiatives that improve finance business processes, decision-making, and productivity. You will translate business needs into practical AI solutions and lead their technical delivery from discovery and architecture through development, evaluation, deployment, and ongoing improvement.
This is a senior individual contributor role with responsibility for technical direction and project outcomes. You will collaborate across business and technology teams and provide technical guidance and mentoring to junior colleagues. People management may be included as business needs evolve, while hands-on technical leadership remains the primary responsibility.
This is a band 8 Remote position for qualified candidates in the US (EST or CST preference).
What you’ll do:
- Lead the technical delivery of AI projects, defining solution architecture, implementation plans, dependencies, and acceptance criteria.
- Partner with finance and other business stakeholders to identify valuable AI use cases, assess feasibility, and establish measurable outcomes.
- Design, build, and integrate AI applications using generative AI, machine learning, enterprise data, and workflow automation as appropriate to the business problem.
- Develop prototypes and production solutions, selecting technologies based on accuracy, reliability, security, scalability, performance, and cost.
- Establish evaluation approaches for AI outputs, including quality, robustness, and appropriate human review.
- Design and implement the data pipelines, APIs, and enterprise integrations needed to support AI solutions.
- Collaborate with IT, architecture, cybersecurity, privacy, and data governance teams to meet applicable requirements throughout development and deployment.
- Apply sound software engineering practices, including version control, code review, testing, documentation, and automated deployment.
- Define monitoring, support, and operational handoff requirements; investigate issues and improve deployed solutions.
- Communicate technical recommendations, tradeoffs, project risks, and results to technical and business audiences.
- Mentor junior data scientists and engineers through design reviews, code reviews, and collaborative problem-solving.
What you’ll need:
- Advanced degree and 6 years of computer science, data science, engineering, or a related technical field and AI experience, or Bachelor’s degree and 8 years of computer science, data science, engineering, or a related technical field and AI experience.
- Demonstrated experience serving as the technical lead for AI or advanced analytics projects, including delivery into production.
- Strong hands-on proficiency in Python and SQL, with experience building maintainable applications and data integrations.
- Practical experience developing generative AI solutions using platforms such as Azure OpenAI or Amazon Bedrock.
- Experience integrating AI models with enterprise data and applications, including retrieval-augmented generation, APIs, and workflow orchestration.
- Ability to evaluate AI solution quality and explain limitations, technical tradeoffs, and deployment considerations.
- Experience with cloud services and data platforms such as AWS, Azure, Snowflake, or Databricks.
- Working knowledge of data architecture, ETL/ELT processes, data quality, and access controls.
- Experience using version control, testing, CI/CD, and collaborative development tools.
- Strong communication skills and the ability to translate business needs into technical requirements and delivery plans.
- Demonstrated ability to guide technical contributors and coordinate delivery across functions
Preferred Qualifications:
- Experience applying AI to processes, analytics, or enterprise productivity.
- Experience with distributed data processing technologies such as PySpark, Apache Spark, and Delta Lake.
- Experience designing and implementing enterprise data models and semantic layers that support consistent business definitions, analytics, and AI applications
- Experience with predictive modeling and statistical analysis
- Experience using Azure DevOps or JIRA within Agile delivery teams.
At Thermo Fisher Scientific, we are committed to fostering a healthy and harmonious workplace for our employees. We understand the importance of creating an environment that allows individuals to excel. Please see below for the required qualifications for this position, which also includes the possibility of equivalent experience:
- Able to communicate, receive, and understand information and ideas with diverse groups of people in a comprehensible and reasonable manner.
- Able to work upright and stationary for typical working hours.
- Ability to use and learn standard office equipment and technology with proficiency.
- Able to perform successfully under pressure while prioritizing and handling multiple projects or activities.
- May require as-needed travel (0-20%).
Location: EST or CST remote US. Relocation assistance is NOT provided.
- Must be legally authorized to work in the United States without sponsorship.
- Must be able to pass a comprehensive background check, which includes a drug screening.
The annual salary range estimated for this position in North Carolina is $138,000 - $208,000 USD. This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy.
See All 27 Remote Staff ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Staff ML Engineer JobsRemote Staff ML Engineer Job Market
Who's Hiring
Top Industries Hiring
- Hospitality & Tourism
- Technology & Software
- Media & Entertainment
What Employers Look For
The qualifications that appear most often in remote staff ML engineer jobs.
- 7 or more years of machine learning or applied research experience with production deployments
- Deep proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX
- Experience designing and operating large-scale distributed training and inference systems
- Strong background in MLOps, including model monitoring, feature stores, and CI/CD pipelines
- Demonstrated ability to mentor engineers and influence technical direction across multiple teams
- Advanced degree in computer science, statistics, or a related quantitative field
Tips for Your Remote Staff ML Engineer Job Search
Apply early to remote roles that fit
Migrate Mate lists remote staff ml engineer openings from across the U.S. in one place, so you can find roles that match your stack and seniority level and apply directly without sifting through mixed location results.
Show async communication as a skill
Remote staff engineers are evaluated on how clearly they think in writing. Include design documents, internal RFCs, or technical write-ups in your portfolio alongside code, since remote hiring managers treat written artifacts as evidence of staff-level influence.
Demonstrate remote ownership on past projects
Frame your resume around outcomes you drove with minimal oversight, naming the ML systems you owned end-to-end, the teams you influenced, and the production metrics that changed. Remote employers at staff level need proof you can lead without in-person coordination.
Prepare for async technical screens
Many remote-first teams use take-home system design problems or recorded architecture walkthroughs instead of live coding sessions. Practice explaining ML design tradeoffs in Loom-style recordings and written Notion or Confluence documents, since those formats mirror real async work.
Remote Staff ML Engineer Jobs: Frequently Asked Questions
How do I get a remote staff ml engineer job?
Target companies that run distributed engineering teams, since they have established workflows for async collaboration and are more likely to trust a staff-level engineer to work independently. Remote employers at this level screen heavily for written communication, self-directed project ownership, and the ability to influence technical direction without in-person presence. A portfolio of shipped ML systems, design documents, or public writing on model architecture decisions strengthens your case considerably.
Which companies hire remote staff ml engineers?
Remote staff ml engineer roles are posted by Airbnb, reddit, and Payabli and others right now, based on current remote listings on Migrate Mate as of November 2026. These openings come from remote-first technology companies, distributed product teams, and enterprise organizations in sectors like cloud infrastructure, fintech, and health technology that have built permanent remote engineering practices.
Can you get a remote staff ml engineer job with no experience?
Yes, but it is harder remotely because employers expect you to operate without close supervision from day one. Remote-first startups and early-stage AI companies occasionally hire junior ML engineers for distributed roles. Without prior professional experience, a strong GitHub portfolio, contributions to open-source ML projects, or a documented personal project with measurable results can substitute for work history and open the door to remote consideration.
Do you need a degree for remote staff ml engineer jobs?
Not always. Remote employers at the staff level weigh demonstrated engineering depth over credentials, so a strong portfolio of ML system design, production deployments, and cross-functional technical leadership can carry more weight than a formal degree. That said, many remote teams at larger companies still list a bachelor's or master's in computer science or a related field as a baseline, so having one removes a screening obstacle early.
Which industries hire the most remote staff ml engineers?
Most remote staff ml engineer openings sit in Hospitality & Tourism, Technology & Software, and Media & Entertainment, per current remote listings on Migrate Mate as of November 2026. These sectors hire staff ml engineers remotely because their products are built by distributed engineering teams that have standardized on async workflows and can support senior-level independent contributors without a central office.
See All 27 Remote Staff ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Staff ML Engineer Jobs