VedyanHire AI & Machine Learning Engineers
Engineers who take generative AI and machine-learning work from prototype to production: RAG assistants, agentic workflows, recommendation systems and MLOps.
Skills we screen for
Retrieval-augmented generation (RAG) and vector databases
Agentic and multi-agent workflows with LangGraph or similar frameworks
LLM platforms: AWS Bedrock, Google Vertex AI, Azure OpenAI
Evaluation, guardrails and cost control for LLM applications
MLOps: model deployment, monitoring and retraining pipelines
Python, data pipelines and cloud infrastructure
Roles we place
GenAI engineerMachine-learning engineerMLOps engineerData scientistAI solutions architect
How you can hire
| Model | How it works |
|---|---|
| W2 | Consultant on Vedyan payroll with tax withholding. |
| C2C | Consultant's own corporation invoices Vedyan. |
| 1099 | Independent contractor, paid gross. |
| C2H | Contract first, then converts to full-time. |
| SOW | Fixed scope and deliverables, milestone billing. |
Frequently asked questions
Do your AI engineers build production systems or prototypes?
We screen for production experience: deployment, monitoring, evaluation, security and cost. Prototypes are easy; we look for engineers who have kept AI systems running for real users.
Which cloud AI platforms do your engineers know?
Most commonly AWS Bedrock, Google Vertex AI and Azure OpenAI, along with open-source models and frameworks such as LangChain and LangGraph.
Can you deliver an AI pilot as a project?
Yes. A Vedyan team can scope, build and hand over a pilot under a fixed statement of work, including evaluation criteria agreed up front.
Ready to build your next team?
Tell us what you're working on. We'll reply within one business day.