Overview
On Site
Depends on Experience
Contract - W2
Contract - Independent
Contract - 5 Year(s)
Skills
Machine Learning (ML)
Algorithms
Amazon Web Services
Apache Kafka
Cloud Computing
Communication
Google Cloud
Google Cloud Platform
Natural Language Processing
Software Development Methodology
GitHub
Job Details
Job Title: Lead Machine Learning Engineer
Location: Davis, CA
Job Type: Contract Long Term
Client: University of California
Description:
- 5+ years of professional experience as a Machine Learning
- Engineer Experience designing, developing, deploying, and supporting machine learning models and platforms for medium to large sized projects
- Experience with the full Software Development Life Cycle (SDLC) of ML models in production
Experience with core ML algorithms including:
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ML domain:
- Natural Language Processing, Computer Vision, Recommendation Systems, Forecasting, Classification
Tools & Platforms:
- Elasticsearch, Kubernetes, Docker, Redis, Apache Kafka, Apache Spark, SQL, NoSQL, Infrastructure as Code (IaC), AWS Lambda Cloud Computing Platforms
Experience with one or more of:
- Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (Google Cloud Platform)CI/CD and DevOps
Experience building CI/CD pipelines using:
- GitHub Actions, TravisCI, Other CI/CD tools
Collaboration and Communication:
- Strong oral and written communication skills, Ability to interact with both technical and nontechnical stakeholders, Able to translate business requirements into technical solutions and documentation
Security and Privacy:
Understanding and application of data privacy and security standards in development
Education:
- Bachelor s degree in computer science, Engineering, Mathematics, or Information Systems
- Equivalent combination of education and experience also considered
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.