Sr Data Scientist / MLOps Engineer

About the Role

Key Responsibilities

• Design, implement, and maintain end-to-end ML pipelines in Azure Machine Learning.
• Develop and manage CI/CD pipelines for ML workflows using GitHub Actions.
• Deploy machine learning models to Azure Kubernetes Service (AKS) or other Azure-hosted endpoints.
• Monitor model performance and data drift; implement automated retraining strategies.
• Work with infrastructure teams to manage compute resources, storage, and security.
• Collaborate with data scientists to transition experimental code into production environments.
• Maintain reproducibility, versioning, and traceability of data, models, and code.
• Ensure best practices in MLOps, security, testing, and observability.

Requirements

• 5+ years of experience in Data Science/Engineering roles.
• Strong SQL and Python skills and experience.

Nice to Have

• 2+ years of experience in MLOps, DevOps, or ML Engineering roles.
• Hands-on experience with Azure Machine Learning, Azure DevOps, Azure Kubernetes Service (AKS).
• Proficient with Git, GitHub, and GitHub Actions workflows.
• Familiarity with containerization using Docker, and orchestration via Kubernetes.
• Experience with model deployment, versioning, and monitoring in production.
• Knowledge of ML lifecycle tools (e.g., MLflow, DVC, Azure ML tracking).
• Experience with IaC tools like Terraform.
• Experience developing and deploying Generative AI and Large Language Models (LLMs) using frameworks such as Azure OpenAI Service.

Qualifications

• Bachelor's degree preferred/specialized training/relevant professional qualification.

Benefits & Perks

• Affordable medical plan options, a 401(k) plan (including matching company contributions), and an employee stock purchase plan.
• No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching.
• Benefit solutions that address the different needs and preferences of our colleagues including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.