Remote AI Research Scientist Jobs
Remote AI Research Scientist jobs are in active demand at remote-first companies and large distributed teams, including employers like CVS Health, Alvarez & Marsal, and Netflix, from junior to senior. Find a role that fits below and apply directly.
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Showing 5 of 425+ Remote AI Research Scientist jobs
Title: AI Engineer
Duration: 6 Months
Location: Remote
Job Description:
Role Summary
We have a capable engineering team working on a complex legacy-to-Python migration and multiple customer-facing platforms. We don't need another developer — we need someone whose primary job is to make the entire team 3-5x faster by building AI-powered automation across every phase of the SDLC: requirements extraction, code generation, testing, defect analysis, and release. This person doesn't just use AI — they architect AI-driven engineering workflows that multiply the output of every developer on the team.
Required Skills (Must-Have):
- AI Agent Development & Orchestration: #1 differentiator. Proven experience building multi-step AI agent workflows for engineering tasks — chaining code analysis, generation, validation, feedback. GitHub Copilot, Claude, LangChain, custom agents, or equivalent.
- SDLC Automation & DevOps: Track record of automating significant portions of the delivery lifecycle — CI/CD, automated testing, code quality gates, release automation (GitHub Actions).
- Python (strong proficiency): Primary codebase is Python — data processing, JSON transformations, modular architecture. Must build tooling and review/generate code at scale.
- Automated Testing Frameworks: AI-augmented regression suites, diff/comparison tooling, scenario-based test generation, golden-file validation. pytest, CI integration.
- Advanced Prompt Engineering: Complex multi-step prompts for code generation, legacy code analysis, business rule extraction. Knows how to structure context, manage token limits, and validate AI outputs.
Requirements
- 7+ years of experience
Preferred Skills
- Legacy code analysis — Parsing unfamiliar proprietary languages to extract business logic via AI
- Java / Spring Boot — Secondary platforms are Java-based
- Elasticsearch, Azure / AKS / Cosmos DB — Platform technologies
- Healthcare data / MDM domain
Key Attributes
- AI-native thinker — Every manual process is an automation opportunity. AI is the primary development engine, not a side tool.
- Force multiplier — Measures success by how much faster they make the entire team, not by their own code output
- Builder of systems — Creates reusable tooling, agent templates, and playbooks the whole team adopts
- Pragmatic and fast — Ships working automation in days, not weeks. Iterates rapidly.
Environment
Python, Java/Spring Boot, Elasticsearch, Azure (AKS, Cosmos DB), GitHub, Jira, HPCC/ECL (legacy) | GitHub Copilot, Claude, SDD, AI-DLC | Agile, 2-week sprints
Title: AI Engineer
Duration: 6 Months
Location: Remote
Job Description:
Role Summary
We have a capable engineering team working on a complex legacy-to-Python migration and multiple customer-facing platforms. We don't need another developer — we need someone whose primary job is to make the entire team 3-5x faster by building AI-powered automation across every phase of the SDLC: requirements extraction, code generation, testing, defect analysis, and release. This person doesn't just use AI — they architect AI-driven engineering workflows that multiply the output of every developer on the team.
Required Skills (Must-Have):
- AI Agent Development & Orchestration: #1 differentiator. Proven experience building multi-step AI agent workflows for engineering tasks — chaining code analysis, generation, validation, feedback. GitHub Copilot, Claude, LangChain, custom agents, or equivalent.
- SDLC Automation & DevOps: Track record of automating significant portions of the delivery lifecycle — CI/CD, automated testing, code quality gates, release automation (GitHub Actions).
- Python (strong proficiency): Primary codebase is Python — data processing, JSON transformations, modular architecture. Must build tooling and review/generate code at scale.
- Automated Testing Frameworks: AI-augmented regression suites, diff/comparison tooling, scenario-based test generation, golden-file validation. pytest, CI integration.
- Advanced Prompt Engineering: Complex multi-step prompts for code generation, legacy code analysis, business rule extraction. Knows how to structure context, manage token limits, and validate AI outputs.
Requirements
- 7+ years of experience
Preferred Skills
- Legacy code analysis — Parsing unfamiliar proprietary languages to extract business logic via AI
- Java / Spring Boot — Secondary platforms are Java-based
- Elasticsearch, Azure / AKS / Cosmos DB — Platform technologies
- Healthcare data / MDM domain
Key Attributes
- AI-native thinker — Every manual process is an automation opportunity. AI is the primary development engine, not a side tool.
- Force multiplier — Measures success by how much faster they make the entire team, not by their own code output
- Builder of systems — Creates reusable tooling, agent templates, and playbooks the whole team adopts
- Pragmatic and fast — Ships working automation in days, not weeks. Iterates rapidly.
Environment
Python, Java/Spring Boot, Elasticsearch, Azure (AKS, Cosmos DB), GitHub, Jira, HPCC/ECL (legacy) | GitHub Copilot, Claude, SDD, AI-DLC | Agile, 2-week sprints
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Find JobsRemote AI Research Scientist Job Market
Who's Hiring
- CVS Health34
- Alvarez & Marsal26
- Netflix19
- Airbnb13
- Block9
Top Industries Hiring
- Technology & Software128
- Consulting & Professional Services56
- Healthcare & Medical Services52
- Investment & Asset Management29
- Accounting & Auditing27
What Employers Look For
The qualifications that appear most often in remote AI research scientist jobs.
- PhD in computer science, machine learning, statistics, or a closely related field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing and running large-scale machine learning experiments
- Publication record in peer-reviewed venues such as NeurIPS, ICML, ICLR, or ACL
- Ability to communicate research findings clearly to both technical and non-technical audiences
- Familiarity with distributed training, cloud compute platforms, and experiment tracking tools
Tips for Your Remote AI Research Scientist Job Search
Lead your resume with publications
Hiring managers for ai research scientist roles scan for peer-reviewed work before anything else. List first-author papers, preprints, and conference proceedings at the top of your resume, ahead of your work history, so reviewers can assess your research output immediately.
Match your specialization to the job description
AI research scientist postings vary widely by domain. A role focused on large language models requires a different portfolio than one in robotics or drug discovery. Tailor your application materials to the specific subdomain listed, not to AI research in general.
Apply early to roles that fit
Migrate Mate lists ai research scientist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a research talk before interviews
Most ai research scientist interviews include a technical presentation on your prior work. Prepare a 20-minute talk on your strongest project that covers the problem, your methodology, results, and what you would do differently, then practice fielding deep follow-up questions on every choice you made.
Surface your GitHub and model benchmarks
Reproducible results and public code repositories carry real weight when you apply. Link to your GitHub, Hugging Face model cards, or benchmark leaderboard entries directly in your resume or cover letter so reviewers can verify your claims without extra steps.
Negotiate research resources, not just compensation
When you reach the offer stage, ask specifically about compute budget, access to proprietary datasets, publication approval processes, and collaboration with external academics. These conditions affect your ability to do the work and your long-term output as a researcher.
Remote AI Research Scientist Jobs: Frequently Asked Questions
How do I get a remote AI research scientist job?
Target companies that already run distributed teams, since they hire remotely by default and know how to onboard someone they never meet in person. Remote AI research scientist employers screen hard for self-direction and clear written communication on top of the core skills, so show evidence you can own work without someone over your shoulder. Apply to the openings above that match your experience.
Which companies hire remote AI research scientists?
Remote AI research scientist roles are posted by CVS Health, Alvarez & Marsal, and Netflix and others right now, based on current remote listings on Migrate Mate as of June 2026. Remote-first firms and large companies running distributed teams post the most remote AI research scientist roles.
Can you get a remote AI research scientist job with no experience?
Yes, but it is harder than an on-site role, because remote work expects you to operate independently from the start. Entry-level remote AI research scientist openings do exist, especially at remote-first companies, and a portfolio of real work helps more than a long resume. Applying broadly to the roles that fit improves your odds.
Do you need a degree for remote AI research scientist jobs?
Not always. Many employers hire remote AI research scientists on demonstrated skills and prior work rather than a specific degree, though some larger companies still prefer one. Showing relevant results matters more than a credential for most remote AI research scientist roles.
Which industries hire the most remote AI research scientists?
The sectors hiring the most remote AI research scientists are Technology & Software, Consulting & Professional Services, and Healthcare & Medical Services, based on current remote listings on Migrate Mate as of June 2026. These sectors run distributed teams and hire AI research scientists remotely most consistently.
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