AI Specialist Jobs
AI Specialist jobs are open across technology, healthcare, finance, and manufacturing, from entry-level analyst to principal and director, with specializations in machine learning engineering, 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 690+ AI Specialist 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 Specialist Jobs by Experience Level
See All 690+ AI Specialist Jobs
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Find AI Specialist JobsAI Specialist Job Market
Who's Hiring
- Meridial142
- Amazon Web Services46
- Booz Allen Hamilton12
- JPMorganChase10
- Samsara6
Top Industries Hiring
- Technology & Software54
- Education17
- Distribution & Wholesale12
- Investment & Asset Management12
- Banking & Financial Services11
What Employers Look For
The qualifications that appear most often in AI specialist jobs.
- Proficiency in Python and machine learning frameworks such as PyTorch or TensorFlow
- Experience designing, training, and deploying machine learning or deep learning models
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for model serving
- Strong foundation in statistics, linear algebra, and probability theory
- Experience with MLOps tools for model versioning, monitoring, and pipeline automation
- Bachelor's or master's degree in computer science, data science, or a related quantitative field
Tips for Your AI Specialist Job Search
Tailor your resume to model types
Hiring managers scan for the specific model architectures you've worked with, such as transformer-based LLMs, diffusion models, or reinforcement learning systems. Name them explicitly in your experience bullets rather than describing AI work in general terms.
Show production deployments, not just experiments
Recruiters for ai specialist roles want evidence that your models left a notebook and ran in production. Quantify throughput, latency improvements, or error-rate reductions from deployed systems rather than listing Kaggle competitions or coursework projects.
Filter openings by the ML stack they use
Many ai specialist postings bury their required tools in the middle of a long description. Search by framework names like PyTorch, TensorFlow, or Hugging Face alongside the job title to surface roles that actually match your hands-on experience.
Apply early to roles that fit
Migrate Mate lists ai specialist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a system design answer for AI pipelines
Most senior ai specialist interviews include a whiteboard or verbal exercise where you design a full ML pipeline from data ingestion to serving. Practice explaining data versioning, feature stores, model registries, and monitoring layers before your first technical screen.
Negotiate on compute access, not just salary
AI specialists often find that GPU cluster access, cloud budget, and dataset licensing matter more to day-to-day productivity than title alone. Ask about compute resources and data infrastructure before accepting an offer so you know what you're actually working with.
AI Specialist Jobs: Frequently Asked Questions
Which companies are hiring the most ai specialists?
The companies hiring the most ai specialists right now include Meridial, Amazon Web Services, and Booz Allen Hamilton, with the largest share of openings in Texas, California, and New York, based on current listings on Migrate Mate as of August 2026. Demand is concentrated in technology, financial services, and healthcare, though manufacturing and logistics employers are adding ai specialist roles at a growing pace.
How many ai specialist jobs are remote?
About 69% of ai specialist openings are fully remote or hybrid as of August 2026, making it one of the more location-flexible technical roles available. Research, NLP engineering, and model evaluation work tends to be most remote-friendly, while roles involving proprietary on-premise hardware or regulated data environments are more likely to require on-site presence.
How do you become an ai specialist?
Start by building a strong foundation in Python, linear algebra, and probability, then work through core machine learning concepts using open datasets to develop real projects you can show. Pursue a degree or structured program in computer science or data science if you haven't already, add hands-on experience with frameworks like PyTorch or TensorFlow, and document at least one end-to-end deployment in a public portfolio before applying.
Can you get hired as an ai specialist with little or no experience?
Entry-level ai specialist roles exist, but they typically require demonstrated technical ability even without a long work history. Build a portfolio of self-directed projects that show model training, evaluation, and deployment rather than just course completions. Target companies with dedicated ML infrastructure teams where junior specialists have structured mentorship, and apply to roles explicitly labeled associate, junior, or entry-level rather than generic ai specialist postings aimed at mid-career candidates.
What does the ai specialist interview process look like?
Most ai specialist interviews begin with a recruiter screen focused on your background and the role, followed by a technical phone screen covering Python, statistics, and ML fundamentals. Later rounds typically include a take-home or live coding exercise involving model training or evaluation, a system design session where you architect an ML pipeline, and a final round with cross-functional stakeholders or senior engineers who assess research judgment and communication.
Where can I find and apply to ai specialist jobs?
You can find and apply to ai specialist jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your skills and experience, then apply directly to each one that fits.
See All 690+ AI Specialist Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI Specialist Jobs