ML Ops Engineer

Job: ML Ops Engineer

Location: Concord, CA

Experience: 12+

Last Round F2F

Note: Please Send Locals who are in California

Overview Tachyon Cortex Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions.

Key Responsibilities

· Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.

· Automate model training, testing, deployment, and monitoring in cloud environments (e.g., Google Cloud Platform, AWS, Azure).

· Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and retraining.

· Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM, documentation, explainability)

· Collaborate with engineering teams to provision containerized environments and support model scoring via low-latency APIs

· Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment

Qualifications

· 10+ Years of professional experience in Software Engineering & 3+ Years in AIML, Machine Learning Model Operations.

· Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).

· Experience with cloud platforms and containerization (Docker, Kubernetes).

· Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks.

· Solid understanding of software engineering principles and DevOps practices.

· Ability to communicate complex technical concepts to non-technical stakeholders.