- 5+ years of Machine Learning experience
- Databricks
- WS Sagemaker
- Python
- SQL
- Client Models, Client Ops experience
- Data preprocessing
- Build and maintain scalable infrastructure for machine learning model & pipeline deployment, including containerization & orchestration.
- Develop and maintain scalable & secure REST APIs for serving multiple machine learning models to various users.
- Collaborate with data scientists and software engineers to ensure seamless integration of Client models into our systems.
- Design and optimize data pipelines, data storage, and data processing systems to support the training and inference processes of machine learning models.
- Build and maintain data and model dashboards to monitor model performance and health in production environments.
- Collaborate with cross-functional teams to identify and address data quality, data governance, and security considerations in the context of Client operations.
- Monitor model performance and health in production environments, establishing and maintaining appropriate monitoring and alerting mechanisms.
- Required
- Bachelor's degree in Computer Science, Data Science, or a related field. A Master's or Ph.D. degree is a plus.
- 5+ years of hands-on experience in Client operations, Client engineering, or related roles.
- Experience with AWS & Databricks cloud platforms, specifically AWS Sagemaker, AWS Jumpstart, & AWS Bedrock.
- Experience with REST API development, AWS Networking Protocols
- Solid understanding of infrastructure components and technologies, including containerization (e.g., Docker) and CI/CD pipelines
- Strong knowledge of software engineering principles and best practices, including version control, code review, and testing.
- Excellent problem-solving skills, with the ability to analyze complex issues and provide innovative solutions in a fast-paced environment.
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders.
- Preferred
- Familiarity with load balancing, EKS (Kubernetes), & latest serving Client Model Serving Techniques (ex. NVIDIA Triton).
- Familiarity with the Hugging Face Diffusers Library
Machine Learning Engineer - Beaverton, United States - Tekfortune Inc
Description
Tekfortune is a fast-growing consulting firm specialized in permanent, contract & project-based staffing services for world's leading organizations in a broad range of industries. In this quickly changing economic landscape, virtual recruiting and remote work are critical for the future of work. To support the active project demands and skills gaps, our staffing experts can help you find the best job for you.
Machine Learning Engineer
DURATION: 9+ month contracts with chance to extend / convert down the road
LOCATION: FULLY remote in the US working PST Hours
Nike does "Dim the lights" where they shut down for 3-4 weeks per year, usually around New Years/Christmas, Memorial Day, and Labor Day. Some teams work through some of these weeks but please make sure candidates are aware of these weeks off with no pay when negotiating with candidates. They should anticipate working about hours per year.
Background: Nike is making a huge investment into GenAI and don't have the time to hire an entire team of FTE's, so want to get started with contractors and perhaps hire some of them as FTE's down the road.
Required Skillset:
- AWS bedrock, LLMs , LLMOps, Computer Vision, Motion Capture
Info Needed to Submit: Resume, email, candidate blurb, MM/DD of birth
Job description:
Responsibilities: