MLOPS with AI

2AI / ML + LLM Engineering

Build, fine-tune, and deploy large language models (OpenAI, Claude, Llama, Gemini, Mistral).

Implement RAG (Retrieval-Augmented Generation) pipelines and embedding-based search.

Manage vector databases : Pinecone, Weaviate, FAISS, Chroma, Redis Vector.

Optimize prompts, context windows, token usage, and LLM inference latency.

Build agent-based workflows using LangChain, LlamaIndex, Haystack.

Deploy AI / ML models using Triton, KServe, Ray Serve, SageMaker, Vertex AI.

MLOps & ML Pipeline Automation

Build end-to-end automated ML pipelines (training testing deployment monitoring).

Implement CI / CD / CT processes using MLflow, Kubeflow, Airflow, DVC, SageMaker Pipelines.

Manage model registries, data versioning, feature stores (Feast, Delta Lake, Hudi).

Set up automated retraining workflows based on drift signals and monitoring triggers.

Optimize GPU / CPU workloads and distributed model training.

Cloud Infrastructure & DevOps

Deploy scalable, secure applications using AWS, GCP, or Azure.

Design systems using Docker, Kubernetes, Helm, Terraform, ArgoCD, GitOps.

Implement autoscaling strategies and GPU orchestration in K8s clusters.

Build robust observability using Grafana, Prometheus, ELK, Jaeger, OpenTelemetry.

Manage secrets and IAM with Vault, KMS, SSM.

5. Security, Compliance & Performance

Apply OWASP Top 10 and secure coding patterns across front-end / back-end / ML systems