AI Jobs
AI jobs are open from new-grad to principal across technology, healthcare, finance, and media, with common specializations in machine learning engineering, natural language processing, and computer vision. Scan the live roles below and apply to whichever ones fit.
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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 Jobs by Experience Level
Top Cities Hiring AIs
Explore AI openings in the cities hiring most right now.
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Who's Hiring
- Booz Allen Hamilton12
- JPMorganChase10
- Citi4
- Leidos4
- Amazon4
Top Industries Hiring
- Technology & Software18
- Education13
- Banking & Financial Services10
- Investment & Asset Management9
- Healthcare & Medical Services5
What Employers Look For
The qualifications that appear most often in AI jobs.
- Proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow
- Experience building, training, and evaluating machine learning or deep learning models
- Familiarity with cloud ML platforms such as AWS SageMaker, Google Vertex AI, or Azure ML
- Strong foundation in statistics, linear algebra, and applied mathematics
- Experience deploying models to production and monitoring model performance over time
- Bachelor's or master's degree in computer science, data science, mathematics, or a related field
Tips for Your AI Job Search
Quantify model impact on your resume
Recruiters for ai roles expect concrete outcomes, not task lists. Replace vague bullets with numbers: latency improvements, accuracy gains, or cost reductions your models delivered. If you can't share proprietary figures, describe the scale of data or users affected.
Match your skills to the job stack
AI job postings vary widely in their required frameworks. Before applying, check whether the role emphasizes PyTorch, TensorFlow, JAX, or cloud-native ML services, then mirror that language in your resume and cover note so your application clears automated screening.
Apply early to roles that fit
Migrate Mate lists ai openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for a technical take-home component
Many ai interview loops include a graded coding or modeling exercise. Ask the recruiter upfront whether one is included, what tools are allowed, and how long it typically takes so you can block the time and set up your environment beforehand.
Address deployment and production experience
Research and production engineering are different skill sets. If you've taken a model past a notebook into a serving pipeline, monitoring setup, or A/B test, call that out explicitly. Employers often filter for this, and candidates without it frequently stall at the hiring-manager screen.
Negotiate scope, not just compensation
In ai roles, the datasets, compute budget, and team structure you'll work with shape your career trajectory as much as salary does. When you reach the offer stage, ask what projects are starting in the next quarter and what the path looks like from your role to staff or principal.
AI Jobs: Frequently Asked Questions
Which companies are hiring the most ais?
The most active employers for ais right now are Booz Allen Hamilton, JPMorganChase, and Citi, and the most openings are in Virginia, Texas, and Maryland, based on current listings on Migrate Mate as of August 2026. Hiring is concentrated in technology, financial services, and healthcare organizations building or scaling internal AI capabilities.
How many ai jobs are remote?
About 43% of ai openings are fully remote or hybrid as of August 2026, making it one of the more flexible technical disciplines. Research-oriented roles and those focused on natural language processing or generative AI tend to have the highest share of fully remote options, while roles requiring access to proprietary hardware or on-site data infrastructure are more likely to require in-person work.
How do you become an AI professional?
Start by building a strong foundation in Python, statistics, and linear algebra through coursework or self-study. Work through end-to-end projects that go beyond tutorials, ideally publishing code publicly so employers can review your work. Develop hands-on experience with training, evaluating, and deploying models, then apply for roles that match your current skill set and grow from there.
Can you get an AI job with little or no experience?
Yes, entry-level and associate ai roles exist specifically for candidates who are early in their careers. The most effective way to compete without professional experience is to build a portfolio of independent projects that demonstrate end-to-end work, from data preparation through model evaluation. Contributing to open-source ai projects and writing publicly about your findings also signals practical capability to hiring managers.
What does the AI interview process look like?
Most ai interview loops begin with a recruiter screen, followed by a technical phone interview covering machine learning fundamentals, statistics, and coding. A take-home assignment or live coding exercise typically comes next, requiring candidates to build or debug a model. Final rounds usually include a system design discussion focused on ml architecture and a series of behavioral interviews with the hiring manager and cross-functional stakeholders.
Where can I find and apply to AI jobs?
You can find and apply to ai jobs on Migrate Mate, which lists current openings from employers across the United States. Search for roles that match your skills and experience level, then apply directly to each listing that fits. New postings are added regularly, so checking back frequently gives you access to the latest opportunities as they open.
See All 224+ AI Jobs
Find roles that match your experience and apply in just a few clicks.
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