Responsibilities
Kforce has a client that is seeking a ML Ops Engineer in San Francisco, CA. Summary: This role is specifically for the Gen AI platform. The Engineer will integrate the MIP and Azure ML. They will be building the orchestration layer. Duties:
- Assist in design, development, test, deploy, maintain, and enhance Machine Learning Pipelines using K8s/AKS based Argo Workflow Orchestration solutions
- Participate and contribute to design reviews with platform engineering team to decide the design, technologies, project priorities, deadlines, and deliverables
- Work closely with Data Lake and Data Science team to understand their data structure and machine learning algorithms
- Implement real time argo workflow pipelines, integrate pipelines with machine learning models, and translate data and model results into business stakeholders Data Lake
- Develop distributed Machine Learning Pipeline for training & inferencing using Argo, Spark and AKS
- Build highly scalable backend REST APIs to collect data from Data Lake and other use-cases/scenarios
- Deploy Application in Azure Kubernetes Service using GitLab CICD, Jenkins, Docker, Kubectl, Helm and Mainfest
- Review code developed by other developers and provide feedback to ensure best practices (e.g., checking code in, accuracy, testability, and efficiency)
- Debug/track/resolve by analyzing the sources of issues and the impact on application, network, or service operations and quality
- Functional, benchmark & performance testing and tuning for the built workflows
- Assess, design & optimize the resources capacities (e.g., Memory, GPU etc.) for ML based resource intensive workloads
Requirements
- Experience in branching, tagging, and maintaining the versions across the different environments in GitLab
- Understanding of ETL pipelines, and ingress/egress methodologies and design patterns
- ML Platform/ML Engineering => 8 out of 10
- Platform Development/Microservices/Arch => 7/10
- Docker/Containers/Kubernetes => 6/10
- Data Science/Machine Learning => 5/10
- Python - must have
- ML tools experience such as AzureML/MLFlow/Databricks/Kubeflow etc. - Deployed and worked on some of these tools
- Azure - Highly preferred to have the experience
- Spark- Good to Have => 5/10
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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