AI/ML & Analytics Platform Engineer

Education

Education: Bachelor's or Master's in Computer Science, Engineering, Data Science, Mathematics, Statistics, Operations Research, or related field.

Key Responsibilities

• Contribute to building AI/ML & Analytics platform, services, and tools across dev, test, and prod environments to accelerate model training, inference, and deployment.
• Build capabilities for batch and real-time workflows at scale with flexible deployment strategies for use cases like low-latency predictions and offline inference.
• Improve platform performance, reduce manual intervention, scale compute, and increase deployment efficiency.
• Collaborate with cloud teams to ensure operational effectiveness, reliability, security, and efficiency.
• Provide technical guidance on monitoring systems like registries and alerting, plus governance frameworks for regulatory compliance.
• Work with cross-functional teams on AI/ML system architecture, deployment pipelines, and solution scaling.
• Champion self-service patterns, IaC, and GitOps for platform development.

Required Technical Skills

• Experience building scalable AI/ML & Analytics platforms for ML Researchers, Engineers, Data Scientists, and Analysts.
• Proficiency in Python, Spark, SQL, and ML frameworks like PyTorch or TensorFlow.
• Strong AWS knowledge, including AI/ML services like SageMaker.
• IaC tools such as Terraform, OpenTofu, CDK, or Pulumi, plus CI/CD pipelines.
• Containerization with Docker or Podman, and orchestration with Kubernetes or Rancher.
• VCS like GitHub or GitLab, CI/CD tools like GitHub Actions or Jenkins, and JIRA.
• Ops fundamentals including registries, observability, monitoring, performance analysis, and cost optimization.

Required Functional/Behavioral Skills

• Hands-on problem-solving for technical and architectural challenges in scalable, secure platforms.
• Automation-first mindset with security consciousness and focus on developer experience.
• Strong communication to engage stakeholders effectively.
• Ability to work collaboratively in cross-functional, agile teams valuing individual development.

Preferred Skills

• Pharma/biotech domain experience.
• Strongly typed languages like C/C++, Java, Go, or Rust.
• Large-scale distributed systems like Ray, Dask, Spark, or HPC like Slurm.
• Data platforms like Databricks, Snowflake, or dbt with Delta, Iceberg, Hudi.
• Real-time streaming like Kafka or Spark Streaming.
• GitOps tools like ArgoCD or Crossplane.
• Multicloud (AWS, GCP, Azure).
• High-performance inference frameworks like ONNX Runtime, TensorRT, or Triton.
• Large-scale CPU/GPU infrastructure with CUDA knowledge.