ML Ops Engineer (Concord, CA - 100% Onsite)

ML Ops Engineer (Concord, CA - 100% Onsite)

We are looking to hire a candidate with the skills sets mentioned and experience for one of our clients within the multinational technology services Industry. This is a
contracting role, 100% onsite in Concord, California.

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., GCP, 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.

Required Qualifications:

• 10+ Years of professional experience in Software Engineering.


• 3+ Years in AIML, and 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).


• Hands-on experience delivering 3-4 end-to-end Production projects.


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


• Solid understanding of software engineering principles and DevOps practices.


• Good communication skills and able to manage stakeholders.

Other Job Details:

• Location: Concord, California (100% Onsite).


• Job Type: C2C or W2.


• Pay Rate: $55/hr. on W2 OR $60/hr. on C2C.

• Docs required: ID proof will be required.