Machine Learning Engineer

The Machine Learning Engineer role within IDEXX’s AI Enablement Team focuses on the infrastructure and production lifecycle for machine learning models that support Clinical and Generative AI solutions. This hybrid position in Portland, ME requires 2 days per week in the office and centers on deploying, serving, and monitoring models in real-world environments.

Key Responsibilities

• Build and maintain scalable infrastructure and pipelines that enable model deployment and production inference (not model development).
• Collaborate with Data Scientists and Product Teams to convert model outputs into robust, production-ready services.
• Support the scalability, performance, and reliability of inference workflows.
• Design and implement data pipelines that support ML enablement workflows.
• Participate in code reviews to maintain quality and follow engineering best practices.
• Use established software design patterns and contribute to architectural discussions.
• Identify and apply practical improvements to ML enablement processes.
• Contribute to an AI Development Platform intended to support the enterprise-wide adoption of AI capabilities.
• Work with Data Engineering and DevOps to build robust processing workflows and pipelines.
• Partner with product management and engineering teams to identify reusable datasets, components, and infrastructure.
• Manage tradeoffs across cost, time, and technical capability when implementing solutions.
• Collaborate with senior team members, learn from their expertise, and share knowledge with peers.
• Contribute to assigned workstreams to deliver successful, timely outcomes.
• Work independently on well-defined problems, escalating ambiguous or high-impact decisions as needed.

Required Qualifications

• 3-5 years of experience in machine learning engineering or a related role.
• Strong programming skills in Python; familiarity with additional languages is a plus.
• Experience building scalable data processing and ML enablement applications.
• Basic knowledge of Spark for data processing.
• Understanding of sound software engineering practices, including testing and CI/CD.
• Working knowledge of AI/ML concepts with some hands-on experience supporting models in production environments.
• Familiarity with ML stacks such as Databricks, Delta Tables, AWS (EC2, S3, SageMaker), and containerization tools like Docker.
• Basic knowledge of data engineering (SQL, NoSQL, Big Data), cloud architecture, and Agile methodologies.
• Good analytical and problem-solving skills with adaptability to evolving technologies.
• Good communication skills for collaboration with data scientists, engineers, and stakeholders.

Technology Stack

Python, Spark, Databricks, Delta Tables, AWS (EC2, S3, SageMaker), Docker, SQL, NoSQL, Big Data, CI/CD, Agile methodologies

Compensation and Benefits

• Base salary range starting at $115,000 per year based on experience.
• Opportunity for an annual cash bonus.
• Health / Dental / Vision benefits available Day-One.
• 5% matching 401k.
• Additional benefits including, but not limited to: financial support, pet insurance, mental health resources, volunteer paid days off, employee stock program, foundation donation matching, and more.

Location and Work Schedule

Portland, ME (hybrid), with 2 days per week in the office.