AI Research Engineer Jobs
AI Research Engineer jobs are open across technology, healthcare, finance, and defense, at every level from new-grad to principal and staff, with specializations in machine learning, natural language processing, and computer vision. Find a role that fits from the openings below and apply directly.
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Showing 5 of 585+ AI Research Engineer jobs
Job Responsibilities:
- Collaborate with the team to design and develop high quality Web applications using Python, Flask, Django, and related technologies.
- Write clean and efficient code, and ensure code maintainability and reusability.
- Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding).
- Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs) using Python-first frameworks.
- Perform code reviews to ensure code quality and consistency.
- Conduct testing to ensure application quality and reliability.
- Create and maintain technical documentation for web applications.
- Participate in project planning, estimation, and prioritization.
- Stay up to date with the latest technologies for Python development.
- Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding checks), and improve system quality iteratively.
- Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices.
Requirement:
- Experience in software development in Python3.
- Decent understanding of the software development/testing life cycle.
- Knowledge of relational databases (e.g. MySQL, PostgreSQL, etc).
- Experience with version control tools, such as Git.
- Experience building RAG solutions (hybrid search, reranking, chunking strategies, embeddings, prompt + schema design).
- Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns.
- Solid knowledge of vector search concepts and at least one vector DB in production.
- Strong engineering practices: code reviews, testing, telemetry, secure-by-design, reliability mindset.
Preferred Qualifications:
- Master’s Degree in Computer Science, Software Engineering, or related field.
- 1+ year professional experience in Python web application development with either Flask or Django.
- Experience in RESTful API development in Python.
- Understanding of Python web application frameworks such as Flask or Django.
- Experience with Cloud services, such as AWS.
- Experience with Vertex AI and GCP fundamentals (IAM, logging/monitoring, Cloud Run/GKE, storage).
- Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion).
- Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and multilingual retrieval.
- Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management.
- Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling).
BeaconFire is an E-verified company and provides equal employment opportunities (visa sponsorship provided).
Job Responsibilities:
- Collaborate with the team to design and develop high quality Web applications using Python, Flask, Django, and related technologies.
- Write clean and efficient code, and ensure code maintainability and reusability.
- Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding).
- Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs) using Python-first frameworks.
- Perform code reviews to ensure code quality and consistency.
- Conduct testing to ensure application quality and reliability.
- Create and maintain technical documentation for web applications.
- Participate in project planning, estimation, and prioritization.
- Stay up to date with the latest technologies for Python development.
- Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding checks), and improve system quality iteratively.
- Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices.
Requirement:
- Experience in software development in Python3.
- Decent understanding of the software development/testing life cycle.
- Knowledge of relational databases (e.g. MySQL, PostgreSQL, etc).
- Experience with version control tools, such as Git.
- Experience building RAG solutions (hybrid search, reranking, chunking strategies, embeddings, prompt + schema design).
- Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns.
- Solid knowledge of vector search concepts and at least one vector DB in production.
- Strong engineering practices: code reviews, testing, telemetry, secure-by-design, reliability mindset.
Preferred Qualifications:
- Master’s Degree in Computer Science, Software Engineering, or related field.
- 1+ year professional experience in Python web application development with either Flask or Django.
- Experience in RESTful API development in Python.
- Understanding of Python web application frameworks such as Flask or Django.
- Experience with Cloud services, such as AWS.
- Experience with Vertex AI and GCP fundamentals (IAM, logging/monitoring, Cloud Run/GKE, storage).
- Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion).
- Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and multilingual retrieval.
- Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management.
- Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling).
BeaconFire is an E-verified company and provides equal employment opportunities (visa sponsorship provided).
AI Research Engineer Jobs by Experience Level
Top Cities Hiring AI Research Engineers
Explore AI research engineer openings in the cities hiring most right now.
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Find AI Research Engineer JobsAI Research Engineer Job Market
Who's Hiring
- Meta21
- JPMorganChase17
- Google16
- ByteDance16
- Booz Allen Hamilton14
Top Industries Hiring
- Technology & Software107
- Education24
- Science & Research24
- Banking & Financial Services14
- Investment & Asset Management14
What Employers Look For
The qualifications that appear most often in AI research engineer jobs.
- Master's or PhD in computer science, machine learning, or a related quantitative field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing, training, and evaluating large-scale machine learning models
- Familiarity with distributed training systems and GPU cluster environments
- Strong mathematical foundation in linear algebra, probability, and optimization
- Demonstrated research output such as publications, preprints, or open-source contributions
Tips for Your AI Research Engineer Job Search
Tailor your resume to model types
Hiring managers scan for the specific model architectures you've worked with, not just 'machine learning experience.' Name the frameworks, model families, and scale of training runs on your resume so reviewers can immediately match your background to their stack.
Build a public research artifact
A preprint, a well-documented GitHub repo, or a reproducible benchmark result carries more weight than coursework for AI research roles. Link to something you built or contributed to so hiring teams can evaluate your thinking before the first screen.
Apply early to roles that fit
Migrate Mate lists ai research engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter by research scope before applying
Some ai research engineer roles are fundamental research positions, others are applied or product-focused. Read job descriptions for phrases like 'publish at top venues' versus 'deploy to production' so you target openings that match the work you actually want to do.
Prepare a paper walkthrough for interviews
Most ai research engineer loops include a deep-dive on a paper you've authored or studied closely. Practice explaining the motivation, methodology, and limitations out loud, including what you'd do differently, because interviewers probe well beyond surface-level summaries.
Negotiate compute access alongside compensation
For research roles, GPU budget and cluster access directly affect what you can accomplish. Ask early in the offer stage about available compute resources, research cycles separate from product work, and publication policy so you understand the real conditions of the job.
AI Research Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most ai research engineers?
The companies hiring the most ai research engineers right now include Meta, JPMorganChase, and Google, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of August 2026. Openings are concentrated at technology companies, defense contractors, and healthcare AI teams building and scaling foundation models.
How many ai research engineer jobs are remote?
About 40% of ai research engineer openings are fully remote or hybrid as of August 2026, making it one of the more remote-accessible engineering specializations. Roles focused on modeling, evaluation, and literature research tend to be the most remote-friendly, while positions involving on-site compute infrastructure or hardware-adjacent research more often require in-person presence.
How do you become an ai research engineer?
Most ai research engineers start with a strong foundation in mathematics and computer science, then deepen expertise through graduate coursework or independent study in machine learning. Building hands-on projects, contributing to open-source models, and producing public research artifacts like preprints or reproducible benchmarks are the steps that move a candidate from eligible to competitive in most hiring processes.
How do you get hired as an ai research engineer with little experience?
Candidates with limited industry experience get traction by publishing or posting reproducible work in a specific subfield, such as fine-tuning language models or benchmarking vision systems, rather than trying to appear broadly qualified. Targeting applied research roles at mid-size companies, contributing to well-known open-source projects, and entering through a research internship or contractor position are the most common entry paths.
What does the ai research engineer interview process look like?
Most ai research engineer interview loops include a recruiter screen, a technical coding round covering algorithms and data structures, a machine learning fundamentals discussion, and a research deep-dive where you walk through a paper you know well or a project you built. Some companies add a system design round focused on ML infrastructure and a final panel with research leads who evaluate scientific thinking and communication.
Where can I find and apply to ai research engineer jobs?
You can find and apply to ai research engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background and the type of research you want to do, then apply directly to each one that fits.
See All 585+ AI Research Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI Research Engineer Jobs