We are looking for a highly skilled, technical, hands-on ML engineer with a solid background in building end-to-end AI/ML applications, exhibiting a strong aptitude for learning and keeping up with the latest advances in AI/ML. The candidate should also be proficient with AI literacy including Gen AI. The ML Engineer is expected to develop AI/ML Engineering Solutions, perform DevOps and work closely with other stakeholders (ML Engineers, Data Scientists, and Data Engineers) with key responsibilities to: + Develop ML Platform to empower Data Scientists to perform end to end ML Ops. + Work actively and collaborate with Data Science teams within Credit IT to design and develop end to end Machine Learning systems. + Lead evaluation of design options, tools, and utilities to build implementation patterns for MLOps using VertexAI in the most optimal ways. + Create solutions and perform hands-on PoCs. + Develop end to end and scalable Generative AI solutions. + Work with Suppliers, Google Skilled Services, and other Consultants as required. + Collaborate with program managers to plan iterations, backlogs, and dependencies across all workstreams to progress the program at the required pace. + Collaborate with Data/ML Engineering architects, SMEs, and technical leads to establish best practices for data products needed for model training and monitoring considering regulatory policy and legal compliance. + Bachelor's degree in computer science or related field. + 8+ years of relevant work experience in solution, application,



and ML engineering, DevOps with deep understanding of cloud hosting concepts and implementations. + Proven expertise with Vertex AI. + Very strong with programming in Python. + Knowledge of SQL (Relational & Non-relational). + 5+ years of hands-on experience in Analytics, MLOps and Engineering Solutions for ML based models. + Knowledge of enterprise frameworks and technologies. + Strong in engineering design patterns, experience with secure interoperability standards and methods, engineering tools and processes. + Strong in containerization using Docker/Podman. + Strong understanding on DevOps principles and practices, including continuous integration and deployment (CI/CD), automated testing & deployment pipelines. + Good understanding of cloud security best practices and be familiar with different security tools and techniques like Identity and Access Management (IAM), Encryption, Network Security, etc. + Understanding of microservices architecture. + Strong leadership, communication, interpersonal, organizing, and problem-solving skills. + Strong in AI Engineering + The candidate needs to possess necessary Cloud experience (necessary) - preferably in GCP. + Demonstrated industry experience in developing end to end production grade AI/ML systems in both Traditional ML and Generative AI. + Proficiency in Agentic AI frameworks. **Preferred:** Relevant certification in ML Engineering in GCP (GCP - Professional Machine Learning Engineer certification)

📌 Lead AI/ML Engineer (Chennai)
🏢 Ford Motor
📍 Chennai