Senior Machine Learning Engineer - Military veterans preferred

Mitchell International


Senior Machine Learning Engineer

US--Remote

Job ID: 25-18242
Type: Regular Full-Time
# of Openings: 1
Category: Software Development
Mitchell International, Inc.

Overview

At Enlyte, we combine innovative technology, clinical expertise, and human compassion to help people recover after workplace injuries or auto accidents. We support their journey back to health and wellness through our industry-leading solutions and services. Whether you're supporting a Fortune 500 client or a local business, developing cutting-edge technology, or providing clinical services you'll work alongside dedicated professionals who share your commitment to excellence and make a meaningful impact. Join us in fueling our mission to protect dreams and restore lives, while building your career in an environment that values collaboration, innovation, and personal growth.

Be part of a team that makes a real difference.

This is a full-time remote position that can be located anywhere in the U.S.

Mitchell, an Enlyte company, is seeking an experienced Machine Learning Engineer to help us build and deploy scalable AI/ML solutions that drive customer and business value, working closely with data scientists, product managers, and engineers to productionize ML models within our broad range of products.

The successful candidate will be a self-starter, capable of architecting and implementing robust ML systems to solve complex production challenges with minimal direction. This candidate will:

• Have excellent engineering skills and in-depth knowledge of ML infrastructure, model deployment, and production system design.
• Be capable of building scalable ML pipeline automation, establishing MLOps best practices, and mentoring engineering teams on ML system architecture.
• Be an excellent communicator, capable of presenting technical solutions to cross-functional teams and enjoy sharing knowledge to expand the overall ML engineering capabilities of our organization.
• Demonstrate commitment to staying current with the latest MLOps tools, infrastructure patterns, and production ML best practices.

• BS in Computer Science or related field.
• Minimum of 5 years of related experience with a Bachelor's degree; or 3 years with a Master's degree
• 3+ years of hands-on experience in building, deploying and maintaining machine learning models in production environments
• Proven experience leading technical initiatives and defining ML infrastructure standards, particularly in greenfield environments
• Extensive experience with ML infrastructure projects involving model serving, ML pipeline automation, monitoring, and MLOps tooling
• Excellent understanding of software engineering principles, system design, and ML model optimization for production environments
• High proficiency with Python programming language and software engineering best practices
• Knowledge of .NET ecosystem is a strong plus given integration with existing product suite
• High proficiency with SQL and experience with Snowflake and data pipeline technologies
• Experience with AWS SageMaker, Airflow, or similar ML platforms is strongly preferred
• Familiarity with ML algorithms strongly preferred
• Strong understanding of cloud infrastructure, containerization (Docker/Kubernetes), and distributed systems
• Demonstrated ability to mentor engineers and establish technical best practices from scratch
• Excellent written and verbal communication skills with the ability to educate and influence technical teams

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