AI Engineer Jobs
AI Engineer jobs are open across technology, healthcare, finance, and media, from new-grad to staff and principal levels, with common specializations in large language models, computer vision, and MLOps. Find a role that fits from the openings below and apply directly.
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About the role
Invonto is a technology company focused on digital transformation, AI, product innovation, and custom software development. We work with organizations to build and improve real-world digital products, from business applications to cloud-based platforms.
We’re looking for an experienced Generative AI Engineer who can turn emerging AI capabilities into practical applications and business solutions.
You’ll work on real-world projects involving large language models, AI-powered applications, intelligent automation, and enterprise integrations. This role is well suited for an engineer who enjoys both exploring new AI technologies and building reliable software around them.
What You’ll Do
- Design and develop AI-powered applications and solutions using generative AI and large language models
- Build custom AI solutions using self-hosted LLM as well as frontier models
- Develop AI capabilities including conversational assistants, intelligent search, document processing, summarization, content generation, and workflow automation
- Design and implement RAG solutions, embeddings, vector search, and AI-powered knowledge systems
- Develop and integrate AI agents and agentic workflows where appropriate
- Integrate AI capabilities with enterprise applications, APIs, databases, and business systems
- Design and evaluate prompts, model configurations, AI workflows, and responses
- Evaluate AI applications for accuracy, reliability, performance, and cost
- Develop prototypes and proof-of-concepts and help move successful solutions into production
- Work with structured and unstructured data to support AI applications
- Collaborate with developers, designers, project managers, and business stakeholders to translate business needs into practical AI solutions
- Contribute to technical architecture and implementation decisions
- Stay current with rapidly evolving AI models, tools, frameworks, and development practices
- Apply responsible AI practices with attention to data privacy, security, accuracy, and appropriate human oversight
What We’re Looking For
- 3+ years of professional software development, AI engineering, or related experience
- Hands-on experience building applications using Generative AI and large language models
- Strong programming experience with Python and/or JavaScript/TypeScript
- Strong understanding of LLMs, prompt engineering, embeddings, vector databases, and RAG
- Experience building REST APIs
- Experience working with databases and structured and unstructured data
- Experience integrating AI capabilities into applications or business workflows
- Understanding of software development lifecycle and engineering best practices
- Ability to evaluate AI-generated results and troubleshoot issues involving accuracy, reliability, latency, and cost
- Strong problem-solving and analytical skills
- Ability to communicate effectively with both technical and non-technical team members
- Ability to work independently as well as collaboratively
- Curiosity and willingness to continuously learn as AI technologies evolve
- Bachelor’s degree in Computer Science, Engineering, AI/ML, or a related field from a U.S. college or university
Nice to Have
Experience with:
- AI agents and agentic workflows
- LangChain, LangGraph, Semantic Kernel, or similar AI frameworks
- Vector databases such as PGVector and Pinecone
- AI evaluation and testing frameworks
- Fine-tuning or adapting AI models
- Multimodal AI, computer vision, or speech technologies
- AWS and/or Azure
- Docker and modern cloud development
- GitHub Copilot, Claude, Cursor, or other AI-assisted development tools
- Enterprise application integration
- CI/CD and DevOps practices
What We Offer
- 85,000–110,000 salary
- Health benefits
- Paid time off
- Flexible work environment
- Opportunity to work on real-world AI and digital transformation projects
- Exposure to emerging AI models, tools, frameworks, and cloud technologies
- Opportunities to work across different industries and business problems
- A collaborative environment with opportunities to learn and grow
Important Employment Information
This is a direct-hire position. We do not accept agency, C2C, or third-party submissions.
Candidates must be residing in the USA. Candidates must be U.S. Citizen or Permanent Resident. We are unable to provide visa sponsorship or accept OPT candidates for this position.
If you’re excited about AI, enjoy turning emerging technology into practical solutions, and want to work on applications that solve real business problems, we’d love to hear from you.
Apply today to join the Invonto team.
Job Type: Full-time
Pay: $85,000.00 - $110,000.00 per year
Benefits:
- Flexible schedule
- Health insurance
- Paid time off
- Tuition reimbursement
Application Question(s):
- Are you a US Citizen or Permanent Resident, as required for this role?
Experience:
- Python Flask: 2 years (Required)
- Dataset preparation: 3 years (Required)
- Python: 5 years (Required)
- API Development: 2 years (Required)
- AI development: 5 years (Required)
- Generative AI: 2 years (Required)
- PyTorch: 2 years (Preferred)
Work Location: Hybrid remote in Bridgewater, NJ 08807
AI Engineer Jobs by Experience Level
Top Cities Hiring AI Engineers
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Who's Hiring
- Google119
- AfterQuery Experts81
- Meta61
- Humana61
- RNB Consultancy58R
Top Industries Hiring
- Technology & Software123
- Consulting & Professional Services19
- Electronics & Hardware15
- Banking & Financial Services15
- Science & Research8
What Employers Look For
The qualifications that appear most often in AI engineer jobs.
- Proficiency in Python and at least one deep learning framework such as PyTorch or TensorFlow
- Experience designing, training, and deploying machine learning models in production environments
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for ML workloads
- Understanding of LLM architectures, prompt engineering, and fine-tuning or RLHF techniques
- Bachelor's or master's degree in computer science, machine learning, statistics, or a related field
- Experience with MLOps tooling including experiment tracking, model versioning, and pipeline orchestration
Tips for Your AI Engineer Job Search
Tailor your resume to each stack
AI engineer job listings vary sharply by stack. A role focused on LLM fine-tuning calls out different tools than one built around real-time inference pipelines. Match your resume's skills section to the exact frameworks each posting names, whether that's PyTorch, JAX, or Ray.
Show models you shipped, not studied
Hiring managers scan for production signals: a model you deployed, latency you reduced, an evaluation benchmark you improved. Link to a GitHub repo, a paper, or a write-up that shows the problem, your approach, and a measurable result. Side projects count if they ran in production.
Apply early to roles that fit
Migrate Mate lists ai engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by your ML domain
Generalist AI engineer titles often hide very narrow scopes: recommendation systems, speech models, or safety and alignment work. Read the responsibilities section, not just the title, to confirm the role sits in your area before you spend time on a tailored application.
Prepare for a system design round
Most senior ai engineer loops include an ML system design interview separate from coding. Practice scoping a training pipeline or an inference architecture end to end: data ingestion, feature engineering, model serving, and monitoring. Talk through tradeoffs explicitly rather than converging on one solution immediately.
Negotiate on compute and data access
Compensation for ai engineers often includes non-salary levers that matter for your work: GPU budget, access to proprietary datasets, and time allocated to research. Ask about these during the offer stage alongside equity and base, especially at startups where infrastructure budgets vary widely.
AI Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most ai engineers?
The companies hiring the most ai engineers right now include Google, AfterQuery Experts, and Meta, with the largest share of openings in California, Texas, and New York, based on current listings on Migrate Mate as of November 2026. Demand is concentrated at large technology companies, AI-native startups, and enterprise software firms expanding their AI product lines.
How many ai engineer jobs are remote?
About 80% of ai engineer openings are fully remote or hybrid as of November 2026, making it one of the more remote-accessible engineering roles. Sub-areas like LLM research, MLOps, and AI infrastructure tend to offer the highest share of remote arrangements, while roles tied to hardware, robotics, or on-site data pipelines are more likely to require in-person presence.
How do you become an ai engineer?
You become an ai engineer by building a foundation in linear algebra, probability, and Python, then working through machine learning fundamentals using hands-on projects. From there, specialize in an area such as NLP, computer vision, or MLOps, and build a portfolio of production-style work you can point to. A degree helps open doors, but demonstrated project experience and open-source contributions carry significant weight in hiring decisions.
How do you get hired as an ai engineer with little experience?
Focus on shipping something real: fine-tune an open-source model, build an end-to-end inference API, or contribute to an open-source ML library. Document what you built, what broke, and how you fixed it. Apply to roles with titles like ML engineer intern, junior AI engineer, or AI associate, which explicitly target early-career candidates. A strong project portfolio often outweighs years of experience at companies actively growing their AI teams.
What does the ai engineer interview process look like?
A typical ai engineer loop runs across several stages: an initial recruiter screen, a technical phone interview covering Python and ML fundamentals, a take-home or live coding assessment, and a full onsite or virtual loop. The loop usually includes a machine learning system design round, a coding round focused on data structures and algorithms, and a behavioral interview. Some companies add a paper discussion or a presentation of a past project.
Where can I find and apply to ai engineer jobs?
You can find and apply to ai engineer jobs on Migrate Mate, which lists current openings from across the United States in one place. Search for roles that match your specialization and experience level, then apply directly to each listing that fits.
See All 3,842+ AI Engineer Jobs
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