Senior Machine Learning Engineer

JOB TITLE : Senior ML Experience : 5 to 8 years Location : Bangalore, Karnataka, India : Position Overview : As a MLE-2, you will design, implement, and optimize AI solutions while ensuring model success. You will lead the ML lifecycle from development to deployment, collaborate with cross-functional teams, and enhance AI capabilities to drive innovation and impact. Key Responsibilities : - Design and implement AI product features. - Maintain and optimize existing AI systems. - Train, evaluate, deploy, and monitor ML models. - Design ML pipelines for experiment, model, and feature management. - Implement A/B testing and scalable model inferencing APIs. - Optimize GPU architectures, parallel training, and fine-tune models for improved performance. - Deploy LLM solutions tailored to specific use cases. - Ensure DevOps and LLMOps best practices using Kubernetes, Docker, and orchestration frameworks. Technical Requirements : - LLM & ML : Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama - LLMOps : MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex, SageMaker, AWS Bedrock, Azure AI - Databases : MongoDB, PostgreSQL, Pinecone, ChromDB - Cloud : AWS, Azure - DevOps : Kubernetes, Docker - Languages : Python, SQL, JavaScript - Certifications (Bonus) : AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert What You"ll Do : - Collaborate with cross-functional teams to design and build scalable ML solutions. - Implement state-of-the-art ML techniques, including NLP, Generative AI, RAG, and Transformer architectures. - Deploy and monitor ML models for high performance and reliability. - Innovate through research, staying ahead of industry trends. - Build scalable data pipelines following best practices. - Present key insights and drive decision-making. What You Need to Succeed : - Masters degree or equivalent experience in Machine Learning. - 3+ years of industry experience in ML, software engineering, and data engineering. - Proficiency in Python, PyTorch, TensorFlow, and Scikit-learn. - Strong programming skills in Python and JavaScript. - Hands-on experience with ML Ops practices. - Ability to work with research and product teams. - Excellent problem-solving skills and a track record of innovation. - Passion for learning and applying the latest technological advancements.