AI ML Developer

Your Role:

Design, build, and productionize scalable ML and GenAI models and pipelines with high reliability and precision.

Develop retrieval-augmented generation (RAG) pipelines and agentic systems using advanced large language models (LLMs).

Fine-tune, optimize, and deploy transformer-based models such as GPT, Llama, and Mistral for enterprise use cases.

Architect and implement multi-agent frameworks, including tool-augmented reasoning, orchestration, and memory management.

Deliver robust APIs and services for ML and GenAI models with performance and cost optimization in mind.

Collaborate with software engineers and DevOps teams to scale AI systems across cloud, hybrid, and on-prem environments.

Drive automation in model deployment, monitoring, retraining, and drift detection for continuous improvement.

Ensure AI solutions adhere to security, compliance, and governance standards.

Stay updated on GenAI, LLM, and AI infrastructure innovations and integrate advancements into product development.

Required Skills and Qualifications:

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

Proven experience in delivering production-grade ML/GenAI applications.

Strong proficiency in Python (3.x) with frameworks such as PyTorch, TensorFlow, and Hugging Face.

Hands-on experience with LLMs and fine-tuning methods (LoRA, PEFT, quantization).

Expertise in RAG pipelines, embeddings, and vector databases (Elastic, Pinecone, Milvus).

Applied knowledge of GenAI frameworks like LangChain, LlamaIndex, Haystack, LangGraph, AutoGen, or Crew.ai.

Understanding of agent-based systems for multi-agent orchestration, tool use, and reasoning loops.

Familiarity with Model Context Protocol (MCP) for secure GenAI integrations.

Experience with cloud-native ML engineering (Azure OpenAI, AWS Bedrock) and container orchestration (Docker, Kubernetes).

Knowledge of Responsible AI practices, transparency, and ethical AI principles.

Proficiency in MLOps practices, including CI/CD for ML, monitoring, retraining, and scaling.