- Minimum 5+ years of experience in designing, developing, and deploying Machine Learning / Deep Learning systems in production.

- Strong hands-on experience with Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.

- At least 1 year of experience in fine-tuning Large Language Models (LLMs) using LoRA/QLoRA and building RAG (Retrieval-Augmented Generation) pipelines.

- Practical experience with MLOps and production-grade systems including Docker, Kubernetes, Spark, model registries, and CI/CD workflows.

Preferred Requirements :

- Prior experience in open-source GenAI contributions, applied LLM/GenAI research, or large-scale production AI systems.

- B.S./M.S./Ph.D. in Computer Science, Data Science, Machine Learning, or a related technical field.

Role and Responsibilities :

- Lead end-to-end machine learning lifecycle activities including model design, training, evaluation, deployment, and scaling.

- Build and manage production-ready ML pipelines with CI/CD, monitoring, testing, and model drift detection.

- Fine-tune LLMs and implement RAG-based systems for enhanced retrieval and reasoning.

- Design and develop agentic workflows for planning, reasoning, and decision-making.

- Create both real-time and batch inference systems using Docker, Kubernetes, and Spark.

- Utilize advanced architectures such as transformers, diffusion models, RLHF, and multimodal systems.

- Work collaboratively with engineering and product teams to integrate AI models into production applications.

- Mentor junior team members and promote best practices in scalable ML systems, MLOps, and responsible AI.

Ideal Candidate Profile :

- Proven experience in production-grade ML/DL system design and deployment.

- Expertise in LLM fine-tuning, RAG pipelines, and vector search tools (e.g., Weaviate, PGVector).

- Strong software engineering background with knowledge of APIs, version control, and testing.

- Familiarity with agent-based development approaches (e.g., ReAct agents, orchestration, function-calling).

- Ability to balance research innovation with production scalability.

- Additional advantage for open-source contributions, GenAI research, or large-scale applied systems.

Location Options : Mumbai / Bengaluru / Hyderabad / Gurugram

Experience Required : 5 - 12 Years

Working Days : 5 Days/Week (Hybrid - 3 Days WFO)

Notice Period : Maximum 60 Days