MLOps Engineer - Artificial Intelligence / Machine Learning

Description :

• Design and implement CI / CD pipelines for AI and ML model training, evaluation, and RAG system deployment (including LLMs, vectorDB, embedding and reranking models, governance and observability systems, and guardrails).
• Provision and manage AI infrastructure across cloud hyperscalers (AWS / GCP), using infrastructure-as-code tools -strong preference for Terraform-.
• Maintain containerized environments (Docker, Kubernetes) optimized for GPU workloads and distributed compute.
• Support vector database, feature store, and embedding store deployments (e.g., pgVector, Pinecone, Redis, Featureform. MongoDB Atlas, etc).
• Monitor and optimize performance, availability, and cost of AI workloads, using observability tools (e.g., Prometheus, Grafana, Datadog, or managed cloud offerings).
• Collaborate with data scientists, AI / ML engineers, and other members of the platform team to ensure smooth transitions from experimentation to production.
• Implement security best practices including secrets management, model access control, data encryption, and audit logging for AI pipelines.
• Help support the deployment and orchestration of agentic AI systems (LangChain, LangGraph, CrewAI, Copilot Studio, AgentSpace, etc.

Must Haves :

Bonus Attributes :

Abilities :

(ref : hirist.tech)