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Machine Learning Engineer

Beaverton, OR, United States

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Apex Systems, is seeking the following. Apply via Dice today!

Job#: 2028235

Job Description:

Apex Systems is working with our client to find multiple Machine Learning Engineers . In this role, you will assist in production to maintain existing models. While you will be working with the Data Science team, this is an Engineering role.

While this will be a fully remote position you will need to be able to work on PST times

Job Description/Responsibilities:

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 ML 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 ML operations.

Monitor model performance and health in production environments, establishing and maintaining appropriate monitoring and alerting mechanisms.

Must-Have/Required

Bachelors degree in Computer Science, Data Science, or a related field. A Masters or Ph.D. degree is a plus.

5+ years of hands-on experience in ML operations, ML 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/Nice to Have

Familiarity with load balancing, EKS (Kubernetes), & latest ML Model Serving Techniques (ex. NVIDIA Triton).

Familiarity with the Hugging Face Diffusers Library

EEO Employer

Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation in using our website for a search or application, please contact our Employee Services Department at or .

Apex Systems is a world-class IT services company that serves thousands of clients across the globe. When you join Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRated's Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico.

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