ML Ops Lead

Please Contact: To discuss this amazing opportunity, reach out to our Talent Acquisition Specialist Bhupendra Chopade at email address Bhupendra.Chopade@generistek.com can be reached on # 630-576-1937. We have Contract role ML Ops Lead for our client at Dallas, TX.. Please let me know if you or any of your friends would be interested in this position. Position Details: ML Ops Lead- Dallas, TX Location : Dallas, TX Project Duration : 6+ Months Contract Pay rate : $65 to $67 an hour on W2 Job Summary • Build & Automate ML Pipelines: Design, implement, and maintain CI/CD pipelines for machine learning models, ensuring automated data ingestion, model training, testing, versioning, and deployment. • Operationalize Models: Collaborate closely with data scientists to containerize, optimize, and deploy their models to production, focusing on reproducibility, scalability, and performance. • Infrastructure Management: Design and manage the underlying cloud infrastructure (AWS) that powers our ML Ops platform, leveraging Infrastructure-as-Code (IaC) tools to ensure consistency and cost optimization. • Monitoring & Observability: Implement comprehensive monitoring, alerting, and logging solutions to track model performance, data integrity, and pipeline health in real-time. Proactively address issues like model or data drift. • Governance & Security: Establish and enforce best practices for model and data versioning, auditability, security, and access control across the entire machine learning lifecycle. • Tooling & Frameworks: Develop and maintain reusable tools and frameworks to accelerate the ML development process and empower data science teams. Requirements • Cloud Expertise: Extensive hands-on experience in designing and implementing ML Ops solutions on AWS. Proficient with core services like Sage Maker, S3, ECS, EKS, Lambda, SQS, SNS, and IAM. • Coding & Automation: Strong coding proficiency in Python. Extensive experience with automation tools, including Terraform for IaC and GitHub Actions. • ML Ops & DevOps: A solid understanding of ML Ops and DevOps principles. Hands-on experience with ML Ops frameworks like Sage maker Pipelines, Model Registry, Weights and Bias, ML flow or Kube flow and orchestration tools like Airflow or Argo Workflows. • Containerization: Expertise in developing and deploying containerized applications using Docker and orchestrating them with ECS and EKS. • Model Lifecycle: Experience with model testing, validation, and performance monitoring. Good understanding of ML frameworks like Py Torch or Tensor Flow is required to effectively collaborate with data scientists. • Communication: Excellent communication and documentation skills, with a proven ability to collaborate with cross-functional teams (data scientists, data engineers, and architects). Process Flows • Mentor and Knowledge transfer to client project team members • Participate as primary, co and/or contributing author on any and all project deliverables associated with their assigned areas of responsibility • Participate in data conversion and data maintenance • Provide best practice and industry specific solutions • Advise on and provide alternative (out of the box) solutions • Provide thought leadership as well as hands on technical configuration/development as needed. • Participate as a team member of the functional team • Perform other duties as assigned. To discuss this amazing opportunity, reach out to our Talent Acquisition Specialist Bhupendra Chopade at email address Bhupendra.Chopade@generistek.com can be reached on # 630-576-19