Data Science & ML Ops Engineer in SF Bay Area - Only Locals

[Mohammad Sazid]

Hello 

Please check the below position and reply back with the details and updated resume if you are interested.

 

Job title: Data Science & ML Ops Engineer

Location: SF Bay Area – Locals Only (San Leandro Preferably)

Duration: Longterm

Visa – All Visa Except GC (No GC Please)

Passport Number is mandatory

 

9+ Years of experience required

Local DL mandatory

 

Overview
Data Science & ML Ops Engineer to drive the full lifecycle of machine learning solutions—from data exploration and model development to scalable deployment and monitoring. This role bridges the gap between data science model development and production-grade ML Ops Engineering.

 

Key Responsibilities

·       Develop predictive models using structured/unstructured data across 10+ business lines, driving fraud reduction, operational efficiency, and customer insights.

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

·       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

Qualifications

·       Strong proficiency in 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.

Thanks,

Max | KLNtek

Lead - Recruitment

Email: m...@klntek.com

US: +1(315) 274-2836

India: +91-9502141494

324 E Foothill Blvd, Ste 206, 91006 Arcadia, California