Machine Learning Engineer

Role - Machine Learning Engineer

Location - Remote (Must be able to work PST time zone)

Contract - 9 Months with a high possibility of extension and conversion

Pay Rate - $61-$71 hourly Depending on experience

****Must be able to apply without Sponsorship****

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, We are looking for those who have executed and engineered solutions

MUST HAVE

• 5+ Years of Machine Learning model build and deployment in production OR 3 + years with a PHD or Masters Degree in this field
• Databricks
• AWS Sagemaker and Databricks
• Python
• SQL
• ML Models, ML Ops experience
• Containerization
• Bachelor's degree in Computer Science, Data Science, or a related field

NICE TO HAVE

• AWS bedrock, LLMs, LLMOps, Computer Vision, Motion Capture
• Master's or Ph.D. degree is a plus.

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

• 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 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 employeeservices@apexsystems.com or 844-463-6178.