Sr. Data Scientist (AI/ML, Deep learning)

Read Carefully before applying!

We are looking for candidates with the following Mandates:

• Strong Senior Data Scientist (AI/ML/GenAI) Profile
• Mandatory (Experience 1) – Must have a minimum of 5+ years of experience in designing, developing, and deploying Machine Learning / Deep Learning (ML/DL) systems in production
• Mandatory (Experience 2) – Must have strong hands-on experience in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Mandatory (Experience 3) – Must have 1+ years of experience in fine-tuning Large Language Models (LLMs) using techniques like LoRA/QLoRA, and building RAG (Retrieval-Augmented Generation) pipelines.
• Mandatory (Experience 4) – Must have experience with MLOps and production-grade systems including Docker, Kubernetes, Spark, model registries, and CI/CD workflows.

Preferred

• Preferred (Core Skill) – Prior experience in open-source GenAI contributions, applied LLM/GenAI research, or large-scale production AI systems
• Preferred (Education) – B.S./M.S./Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.

Office Location:

Mumbai. Hyderabad, Gurugram, Bangalore

Role & Responsibilities

We are hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems — including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.

Responsibilities:

• Own the full ML lifecycle: model design, training, evaluation, deployment
• Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
• Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
• Build agentic workflows for reasoning, planning, and decision-making
• Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
• Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines
• Collaborate with product and engineering teams to integrate AI models into business applications
• Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices

Ideal Candidate

• 5+ years of experience in designing, deploying, and scaling ML/DL systems in production
• Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
• Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
• Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows
• Strong software engineering background with experience in testing, version control, and APIs
• Proven ability to balance innovation with scalable deployment
• B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
• Bonus: Open-source contributions, GenAI research, or applied systems at scale

Job Type: Full-time

Pay: ₹3,500,000.00 - ₹4,600,000.00 per year

Benefits:

• Work from home

Application Question(s):

• Is your current CTC more than 20LPA?
• Do you have the following: Must have a minimum of 5+ years of experience in designing, developing, and deploying Machine Learning / Deep Learning (ML/DL) systems in production

Work Location: In person