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Lead - AI/ ML/ GenAI
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Title: Technical Lead (AI/ML/GenAI)
Job Description:
We are seeking a highly skilled and innovative Technical Lead ( AI/ML/GenAI) with strong hands-on experience in Agentic AI, Machine Learning, and Cloud Platforms like AWS and Databricks. The ideal candidate will be proficient in building intelligent systems using agentic frameworks to deliver scalable, production-grade solutions such as chatbots and autonomous agents.
Key Responsibilities:
- Lead the design, development, and deployment of advanced machine learning models and algorithms for various applications.
- Build and optimize chatbots and autonomous agents using LLM endpoints and frameworks like LangChain, Semantic Kernel, or similar.
- Implement vector search using technologies such as FAISS, Weaviate, Pinecone, or Milvus for semantic retrieval and RAG (Retrieval-Augmented Generation).
- Collaborate with data engineers and product teams to integrate ML models into production systems.
- Monitor and maintain deployed models, ensuring performance, scalability, and reliability.
- Conduct experiments, A/B testing, and model evaluations to improve system accuracy and efficiency.
- Stay updated with the latest advancements in AI/ML, especially in agentic systems and generative AI.
- Ensure robust security, compliance, and governance, including role-based access control, audit logging, and data privacy controls.
- Collaborate with data scientists, ML engineers, and product teams to deliver scalable, production-grade GenAI solutions.
- Participate in code reviews, architecture discussions, and continuous improvement of the GenAI platform.
Required Skills & Qualifications
- 8+ years of experience in Machine Learning, Deep Learning, and AI system design.
- Strong hands-on experience with Agentic AI frameworks and LLM APIs (e.g., OpenAI)
- Certifications in AI/ML or cloud-based AI platforms (AWS, GCP, Azure).
- Proficiency in Python and ML libraries like scikit-learn, XGBoost, etc.
- Experience with AWS services such as SageMaker, Lambda, S3, EC2, and IAM.
- Expertise in Databricks for collaborative data science and ML workflows.
- Solid understanding of vector databases and semantic search.
- Hands-on experience with MLOps including containerization (Docker, Kubernetes), CI/CD, and model monitoring along with tools like MLflow,
- Experience with RAG pipelines & LangChain.
- LLM orchestration, or agentic frameworks.
- Knowledge of data privacy
- Exposure to real-time inference systems and streaming data.
- Experience in regulated industries such as healthcare, biopharma
- Proven ability to scale AI teams and lead complex AI projects in high-growth environments
- Oil & Gas, refinery operations & financial services exposure is preferred
- Master’s/ bachelor’s degree (or equivalent) in computer science, mathematics, or related field
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