Job Opening || Sr MLop engineer || (San Leandro (Bay area)) || Need Local

[Piyush Parsai]

Hello,

My name is Piyush Parsai, and I am a Technical Recruiter for K-Tek Resourcing.
 
We are searching for Professionals below business requirements for one of our clients. Please read through the requirements and connect with us in case it suits your profile.

Please see the Job Description and if you feel Interested then send me your updated resume at piyush...@ktekresourcing.com  

Please Don't share an already submitted profile with HCL,
GC Candidate will work on W2 for this position.
Need Only Local candidates from CA with DL proof.

Job Title: Sr MLop engineer

Location:  San Leandro (Bay area) 

Duration: Long Term

implementation Partner: HCL America

Job Description (Posting).

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.

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Thanks & Regards
Piyush Parsai | LinkedIn
US-Canada IT Recruiter | KTEK Resourcing
piyush...@ktekresourcing.com