Senior Machine Learning Engineer, Worldwide Product Marketing

What you'll do

• Design and implement advanced ML infrastructure frameworks to accelerate model development and delivery.
• Build and maintain automated pipelines for model training, evaluation, versioning, and deployment.
• Establish model observability, incident response, prompt versioning, and feedback loops to ensure model health.
• Enforce model governance, validation standards, and best practices to ensure reproducibility and compliance.
• Identify and resolve bottlenecks in ML workflows to improve system reliability, latency, and throughput.
• Use LLM-based tools to automate repetitive tasks, generate tests, and draft technical documentation.
• Implement CI/CD principles for model integration, deployment, and monitoring across the ML lifecycle.

What we're looking for

• Bachelor's Degree in Software Engineering, Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or a related field.
• 8 years of experience in software engineering with demonstrated experience in large-scale software system design and implementation.
• Proven track record of shipping and maintaining production-grade ML systems end-to-end.
• Strong experience with distributed systems, databases (SQL/NoSQL), cloud platforms (AWS, Azure, or GCP), and Kubernetes.
• Hands-on experience with MLOps tooling such as Ray, MLflow, Kubeflow, SageMaker, or Vertex AI.
• Proficiency in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience building and managing CI/CD pipelines for ML workflows using tools such as Jenkins, GitHub Actions, or ArgoCD.
• Strong understanding of data pipeline orchestration tools such as Airflow or Prefect.