Senior Machine Learning Engineer - (15 - 30 Joiner Only)

Job description

Role: Senior Machine Learning Engineer Experience Level: 4 to 7 Years Work location: Mumbai, Bangalore & Trivandrum Role & Responsibilities: • Hands-on Development: Write clean, modular, and highly optimized Python code. Build, train, fine-tune, and deploy statistical ML, Deep Learning, NLP, and Generative AI models. • AI System Design & Representation: Design scalable, robust, and end-to-end AI architectures. You must be able to visually represent your system designs (using UML, block diagrams, or flowcharts) and clearly explain the reasoning behind your architectural choices and trade-offs. • Generative AI & Agentic Systems: Build and optimize state-of-the-art Generative AI applications, advanced Retrieval-Augmented Generation (RAG) pipelines, and Agentic AI workflows. • MLOps & Production Engineering: Set up and maintain production-grade MLOps pipelines including CI/CD, automated testing, model registry, monitoring, and retraining frameworks. • Technical Leadership & Mentoring: Act as a technical anchor for the team. Guide and mentor junior engineers, perform rigorous code reviews, and champion software engineering best practices. • Client Engagement & Reasoning: Lead technical discussions with clients. Clearly articulate complex technical concepts, updates, risks, and blockers to both technical and non-technical audiences. You must be able to justify your technical decisions with strong analytical reasoning. Skills expectation: • Must have: • Experience: 4 to 7 years of professional experience in Machine Learning, Deep Learning, and Software Engineering. • Strong Programming Foundations: • Exceptional proficiency in Python, with a deep understanding of class-based, object-oriented, and modular coding standards. • Strong proficiency in SQL for querying, processing, and analyzing complex, large-scale datasets. • Comprehensive understanding of coding standards, Git-based version control, and CI/CD practices. • Core ML & Deep Learning: • Hands-on experience developing and deploying statistical ML models (regression, classification, clustering). • Strong theoretical and practical understanding of Deep Learning architectures, particularly Transformers, CNNs, and RNNs. • Experience in Natural Language Processing (NLP) including text embeddings, tokenization, and sequence-to-sequence models. • Generative AI & Agentic AI: • Practical experience designing and deploying Generative AI solutions and LLM-based applications. • Hands-on implementation of advanced RAG (Retrieval-Augmented Generation) pipelines. • Deep familiarity and hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Chroma, Qdrant). • Hands-on experience with Agentic AI Frameworks (e.g., LangChain, LlamaIndex, CrewAI, AutoGen) for multi-agent workflows and tool-use. • AI System Design & Technical Reasoning: • Proven ability to design scalable AI systems from scratch. • Ability to visually diagram and represent architecture designs and explain technical trade-offs with deep, structured reasoning. • Frameworks & Tools: • Strong hands-on experience with PyTorch or TensorFlow. • MLOps Basics: • Experience with model tracking, monitoring, retraining, and production deployment strategies. • Good to have: • Domain Expertise: Previous experience working in the Healthcare & Life Sciences domain (familiarity with HIPAA, clinical data standards, or healthcare compliance is a huge plus). • Databricks & PySpark: • Experience using Databricks for model development, tracking, and collaboration. • Hands-on experience with PySpark for distributed data processing and large-scale feature engineering. • Agile Methodologies: Experience working in Agile/Scrum environments. Behavioural skills: • Technical Reasoning & Depth: Ability to explain complex technical decisions, architecture designs, and model choices under deep probing (explaining the "why", not just the "how"). • Visual Communication: Comfort in using visual tools to present and explain complex system integrations. • Client-Facing Presence: A pleasant, charismatic, and articulate communication style. Ability to lead technical discussions with clients, address risks, and resolve blockers. • Mentorship: Passion for guiding junior engineers and fostering a culture of continuous learning and high engineering standards. What is in it for you: • Cutting-Edge Stack: Work with the latest 2026 AI/ML innovations, including Agentic AI, LLMs, and advanced MLOps. • End-to-End Ownership: Own your deliverables from initial concept and system architecture to production deployment. • Sponsored Certifications: Opportunities to get sponsored certifications across major cloud providers (GCP, AWS, Azure) and tools (Databricks, Tableau, etc.). • Accelerated Growth: Join a fast-growing, award-winning AI-first organization with a highly collaborative and energetic work culture.