MLOps Engineer - Helix

Overview

What We Do CNXN Helix Center at Connection Inc. is at the forefront of AI innovation, offering cutting-edge solutions that redefine the boundaries of artificial intelligence and data management. We are dedicated to helping our clients navigate the complexities of AI integration, ensuring they stay ahead in a rapidly evolving technological landscape. Our commitment to excellence, innovation, and strategic growth makes us an industry leader. Visit us at www.connection.com/helix.

Who We Are Our team is made stronger by a multitude of backgrounds, experiences, and perspectives. It’s what makes Connection unique—what drives us to innovate and create technology solutions that stand apart from the crowd. We’d love for you to be a part of that fabric, to share your ideas and experiences with a team that thrives on fresh thinking, creativity, and helping others.

Why You Should Join Us You’ll find supportive teammates and a rewarding career at Connection—plus great benefits. We take pride in supporting employees with a total rewards package that provides financial, emotional, and physical resources for you and your family. Our compensation, 401k plans, medical insurance, and other benefits are progressive and competitive. We value the importance of our employees’ emotional wellbeing. To support employees, we provide free therapy visits, mental health coaching and tools, and meditation resources. You’ll also enjoy a generous paid time off package that includes not only vacation and sick time, but also Wellness and Volunteer Time Off days.

Position Overview

Reporting to the VP of Core Engineering at CNXN Helix, relying on experience and judgement to plan and accomplish goals, the Machine Learning Operations (ML Ops) Engineer is responsible for operationalizing CNXN Helix's AI and machine learning initiatives. The ML Ops Engineer collaborates with data scientists and software engineers to streamline the deployment and management of Machine Learning models. The ML Ops Engineer ensures that the company's AI solutions are scalable, reliable, and efficient, directly impacting the success of our clients. Primary responsibilities include developing and optimizing CI/CD pipelines for Machine Learning model deployment, managing and scaling Machine Learning infrastructure using Kubernetes and Docker, and collaborating with enterprise authentication services to ensure compliance with security protocols. This role also establishes system monitoring and creates dashboards for service health, maintains up-to-date documentation of systems and processes, and works with cross-functional teams to resolve technical issues and implement solutions. Additionally, the ML Ops Engineer must stay current with emerging Machine Learning tools and methodologies to drive innovation within the team.

This is a remote or hybrid opportunity preferably based near our corporate offices in Merrimack, NH, or Boston or New York metropolitan areas.

Responsibilities

• Automates, develops and optimizes CI/CD pipelines for ML model deployment.
• Manages and scales Machine Learning infrastructure using Kubernetes and Docker.
• Collaborates with enterprise authentication services and ensures compliance with security protocols.
• Establishes system monitoring and creates dashboards for service health.
• Documents and maintains up-to-date documentation of systems and processes.
• Collaborates with cross-functional teams to resolve technical issues and implement solutions.
• Stays current with emerging Machine Learning tools and methodologies.

Compensation

Min: USD $104,996.00/Yr.
Max: USD $135,445.00/Yr.

Qualifications

• Bachelor's degree required or equivalent combination of education and work experience.
• Minimum 6 years related experience.
• Practical experience with Machine Learning model development and deployment. Direct experience in scripting and coding.
• Proficient with TensorFlow, PyTorch, and other Machine Learning frameworks.
• Expert in Docker and Kubernetes.
• Strong scripting skills in Bash or Python.
• Experience with GitLab CI/CD pipelines.
• Familiarity with deploying to on-premises (Dell or HPE Stack) and cloud infrastructure (AWS, Azure, GCP).
• Experience with Jira, Confluence, and monitoring tools. KubeFlow, MLFlow.
• Real world Generative and Predictive foundational experience preferred.
• Knowledge in identity, security, access management, workflow and/or developer-facing products preferred.
• Direct experience working with cross-organizational teams.
• Experience in AI technology policy, compliance, trust and safety policy a plus.
• OpenShift experience is a plus.
• Excellent troubleshooting abilities.
• Ability to work unsupervised and manage time effectively.
• Strong verbal and written communication skills.
• Collaborative mindset and ability to work in a team.