Senior Machine Learning (MLOps) 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 and manage model observability, incident response, prompt versioning, and feedback loops.
• 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.
• Integrate LLM-based tools to automate repetitive tasks, generate documentation, and accelerate development cycles.
• Manage CI/CD pipelines and data orchestration for production-grade machine learning systems.

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 expertise in large-scale system design and implementation.
• 10 years of experience building high-throughput, scalable applications or machine learning models in production environments.
• Proven track record of shipping and maintaining production-grade ML systems end-to-end.
• Proficiency in Python and familiarity with frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with distributed systems, databases (SQL/NoSQL), cloud platforms (AWS, Azure, or GCP), and Kubernetes.
• Hands-on experience with MLOps tools like Ray, MLflow, Kubeflow, SageMaker, or Vertex AI.
• Experience building CI/CD pipelines for ML workflows and using data pipeline orchestration tools like Airflow or Prefect.