Veralto - AI/ML Platform Engineering Specialist

We are looking for an AI / ML Platform Engineer to design, build, and evolve our next-generation machine learning and generative AI infrastructure. This role focuses on enabling scalable, reliable, and automated AI development through a modern MLOps platform primarily on AWS, but adaptable across multi-cloud environments. The ideal candidate combines deep software and platform engineering expertise with strong knowledge of MLOps practices and AI/LLM ecosystem tooling. You will partner closely with data science, AI, and product engineering teams to accelerate model delivery and operational excellence through infrastructure, tooling, and platform services. Role is Hybrid and its preferable to have incumbent based in Bangalore.

In this role, a typical day will look like :

• Develop, improve, and maintain the MLOps platform to enable scalable, reproducible, and observable machine learning and generative AI workflows.

• Design and operate core ML infrastructure (feature stores, model registries, CI/CD pipelines, and data pipelines) using AWS services such as SageMaker, ECS/EKS, Lambda, and Step Functions.

• Enable and support AI and ML development teams, providing best practices, tooling, and technical guidance on leveraging the platform for training, fine-tuning, and deployment.

• Drive technology and architecture decisions across the ML stack, including frameworks, data processing, orchestration, and monitoring tools.

• Collaborate with AI engineering teams to integrate LLMs and generative AI capabilities into products through standardized, secure, and auditable infrastructure.

• Ensure platform scalability, reliability, and compliance by applying DevOps, infrastructure-as-code (IaC), and observability best practices.

• Continuously evaluate and integrate emerging technologies (e.g., LangChain, Ray, MLflow, Kubeflow, Hugging Face) to enhance developer productivity and operational efficiency.

Required Skills & Qualifications :

• Bachelor s or Master s degree in Computer Science, Software Engineering, or related field.

• 4+ years of experience in ML/AI platform or infrastructure engineering, preferably in enterprise or SaaS environments.

• Strong experience with AWS cloud services (SageMaker, ECS/EKS, S3, CloudFormation/Terraform, Step Functions, Lambda).

• Expertise in MLOps frameworks and tools (MLflow, Kubeflow, Vertex AI, Azure ML, or equivalent).

• Solid software engineering background with proficiency in Python, containerization (Docker), and Kubernetes orchestration.

• Proven ability to design and operate scalable data and ML infrastructure with a focus on automation, observability, and governance.