Senior AI Engineer: End-to-End ML & MLOps on Azure

VySystems; United States; Remote; USD 150,000 - 220,000; Full time

Job summary

VySystems in United States seeks a senior Developer for AI Development & Engineering to design, build, and operate production AI systems end to end. You will work across the full AI stack: classical machine learning, deep learning, and modern generative AI (LLMs, RAG, and agentic workflows).

You will turn ambiguous business problems into AI capabilities our users trust, taking ownership from data through deployment, monitoring, and iteration.

Qualifications

• Bachelor’s or Master’s in CS/ML/DS or equivalent practical experience.
• 4+ years software engineering with 2+ years shipping ML/AI systems.
• Proficiency in Python and core ML libraries (PyTorch/TensorFlow).
• Experience deploying LLM-based apps and RAG workflows.
• Hands-on with Azure, containers, and CI/CD pipelines.

Responsibilities

• Design, train, evaluate, and ship ML/DL models for business problems.
• Build LLM-powered apps using Claude, Azure OpenAI, OpenAI, or equivalents.
• Develop RAG systems with embeddings, vector stores, and re-ranking.
• Create agentic workflows with guardrails and human-in-the-loop review.
• Apply prompt engineering and evaluation metrics; ensure observability.
• Maintain data pipelines on Azure with data quality and lineage.
• Productionize models with MLOps: retraining, drift detection, rollback.
• Review code and mentor engineers in AI-assisted development.
• Collaborate with product, security, and business stakeholders.

Skills

Python programming

ML/DL model building

LLM/RAG deployment

CI/CD pipelines

Azure / cloud deployment

Git / code reviews

Team collaboration

Observability & safety

Education

Bachelor’s or Master’s in CS/ML/DS

Tools

PyTorch

TensorFlow

scikit-learn

pandas

NumPy

Git

Azure DevOps

Docker

Kubernetes

Terraform / Bicep

Job description

VySystems in United States seeks a senior Developer for AI Development & Engineering to design, build, and operate production AI systems end to end. You will work across the full AI stack: classical machine learning, deep learning, and modern generative AI (LLMs, RAG, and agentic workflows).

You will turn ambiguous business problems into AI capabilities our users trust, taking ownership from data through deployment, monitoring, and iteration.