Lead Assistant Manager

3 days ago

Pune, Maharashtra, India EXL Full time ₹ 20,00,000 - ₹ 25,00,000 per year
Description
Lead Assistant Manager – Data Scientist (NLP & Generative AI) Location: PAN India / Remote Employment Type: Full-time About the Role We are looking for a motivated Data Scientist with 5+ years of experience in machine learning and data science, focusing on NLP and Generative AI. You will contribute to the design, development, and deployment of AI solutions centered on Large Language Models (LLMs) and agentic AI technologies, including Google ADK, Agent Engine, and Gemini. This role involves working closely with senior leadership to build scalable, real-time inference systems and intelligent applications. Key Responsibilities Lead the architecture, development, and deployment of scalable machine learning and AI systems centered on real-time LLM inference for concurrent users. Design, implement, and manage agentic AI frameworks leveraging Google Adk, Langgraph or custom-built agents. Integrate foundation models (GPT, LLaMA, Claude, Gemini) and fine-tune them for domain-specific intelligent applications. Build robust MLOps pipelines for end-to-end lifecycle management of models—training, testing, deployment, and monitoring. Collaborate with DevOps teams to deploy scalable serving infrastructures using containerization (Docker), orchestration (Kubernetes), and cloud platforms. Drive innovation by adopting new AI capabilities and tools, such as Google Gemini, to enhance AI model performance and interaction quality. Partner cross-functionally to understand traffic patterns and design AI systems that handle real-world scale and complexity. Required Skills & Qualifications Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related fields. 5+ years in ML engineering, applied AI, or data scientist roles. Strong programming expertise in Python and frameworks including PyTorch, TensorFlow, Hugging Face Transformers. Deep experience with NLP, Transformer models, and generative AI techniques. Hands-on experience deploying AI models to concurrent users with high throughput and low latency. Skilled in cloud environments (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG). Experience with agentic AI using Adk, LangChain, Langgraph and Agent Engine Preferred Qualifications Experience with Google Gemini and other advanced LLM innovations. Contributions to open-source AI/ML projects or participation in applied AI research. Knowledge of hardware acceleration and GPU/TPU-based inference optimization. Exposure to event-driven architectures or streaming pipelines (Kafka, Redis).

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