Senior AI/ ML Platform Engineer Specialist

Job Description:

Responsibilities

• Develop, improve, and maintain the MLOps platform to support scalable, reproducible, and observable machine learning and generative AI workflows.
• Design and operate core ML infrastructure including 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 architecture and technology decisions across the ML stack, including frameworks, orchestration, data processing, and observability tools.
• Collaborate with AI engineering teams to integrate LLMs and generative AI capabilities into products using secure, standardized, and auditable infrastructure.
• Continuously evaluate and adopt emerging tools and technologies such as LangChain, Ray, MLflow, Kubeflow, and Hugging Face to improve platform capability and developer productivity.

Qualification & Experience

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• 5+ years of experience in ML/AI platform engineering, infrastructure engineering, or MLOps, preferably in enterprise or SaaS environments.
• Strong hands-on experience with AWS cloud services, including SageMaker, ECS/EKS, S3, Lambda, Step Functions, and Terraform/CloudFormation.
• Proficiency in Python, Docker, and Kubernetes for building and operating scalable ML infrastructure.
• Experience with MLOps tools/frameworks such as MLflow, Kubeflow, Vertex AI, Azure ML, or equivalent, along with familiarity in LLM infrastructure, vector databases, and RAG-based systems.