Remote Sr Staff Machine Learning Engineer Jobs
Remote Sr Staff Machine Learning Engineer jobs are open across the U.S. at remote-first firms and distributed engineering teams in sectors like technology, fintech, and healthcare. Employers hiring remotely right now include Airbnb, reddit, and Payabli. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 27+ Remote Sr Staff Machine Learning 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 Sr Staff Machine Learning Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsRemote Sr Staff Machine Learning 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 sr staff machine learning engineer jobs.
- PhD or Master's degree in computer science, statistics, or a closely related field
- 8 or more years of industry experience building and shipping production machine learning systems
- Deep expertise in distributed training frameworks such as PyTorch, TensorFlow, or JAX
- Experience designing and operating large-scale ML infrastructure including feature stores and model serving
- Demonstrated technical leadership across cross-functional teams including research, engineering, and product
- Proficiency in MLOps tooling including experiment tracking, model registries, and CI/CD pipelines for ML
Tips for Your Remote Sr Staff Machine Learning Engineer Job Search
Demonstrate async leadership in your application materials
Remote sr staff machine learning engineers are expected to lead technical direction across time zones without real-time coordination. Highlight specific instances where you drove ML architecture decisions, unblocked distributed teams, or produced written design documents that others executed from.
Apply early to remote roles that fit
Migrate Mate lists remote sr staff machine learning engineer openings from across the U.S. in one place, so you can find roles that match your skills and apply directly without sorting through unrelated listings.
Build a public record of technical depth
Remote hiring teams for sr staff ML roles can't evaluate you in person, so they rely on what they can find. Publish ML system designs, contribute to open-source frameworks, or share architecture write-ups that demonstrate the scale and complexity of the problems you've solved.
Prepare for distributed-team interview formats
Remote sr staff ML interviews often include asynchronous take-home system design exercises and written technical assessments alongside live sessions. Practice articulating ML architecture tradeoffs clearly in writing, not just verbally, since written communication is a core sr staff remote skill.
Remote Sr Staff Machine Learning Engineer Jobs: Frequently Asked Questions
How do I get a remote sr staff machine learning engineer job?
Target remote-first companies and distributed engineering organizations that have built their workflows around async collaboration, since those teams are most likely to hire sr staff machine learning engineers without requiring office presence. Remote employers at this level screen heavily for self-direction, clear written communication, and the ability to drive large-scale ML systems and mentor others without in-person oversight. A strong portfolio of shipped models, published research, or open-source contributions signals you can execute independently from day one.
Which companies hire remote sr staff machine learning engineers?
Employers currently hiring remote sr staff machine learning engineers include Airbnb, reddit, and Payabli, per current remote listings on Migrate Mate as of November 2026. The bulk of remote openings at this level come from remote-first technology companies, fintech platforms, and healthcare AI firms that run fully distributed engineering teams.
Can you get a remote sr staff machine learning engineer job with no experience?
Yes, but remote entry paths into sr staff-level ML roles are narrow because distributed teams expect you to operate with significant autonomy from the start. Your best opening is contributing to open-source ML projects, building and sharing reproducible end-to-end pipelines, or completing advanced ML engineering coursework with published results. Remote-first startups and smaller AI teams are more willing to weigh demonstrated project work over formal experience than large enterprises are.
Do you need a degree for remote sr staff machine learning engineer jobs?
Not always, though a graduate degree in computer science, statistics, or a related field is common at the sr staff level. Remote employers at this tier weigh your ability to design and scale ML systems, lead technical direction, and communicate complex decisions in writing just as heavily as credentials. A strong publication record, significant open-source work, or a portfolio of high-impact shipped systems can offset or substitute for a formal degree at many remote-first organizations.
Which industries hire the most remote sr staff machine learning engineers?
Most remote sr staff machine learning engineer openings sit in Hospitality & Tourism, Technology & Software, and Media & Entertainment, per current remote listings on Migrate Mate as of November 2026. Those sectors rely on distributed engineering teams to build and maintain large-scale ML infrastructure, which makes remote sr staff machine learning engineers a natural fit for their operating model.
See All 27 Remote Sr Staff Machine Learning Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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