Machine Learning Engineer

The Machine Learning Engineer role within IDEXX’s AI Enablement Team focuses on the infrastructure and pipelines that deploy, serve, and monitor machine learning models in production. This hybrid position is based in Portland, ME and requires 2 days per week in the office.

Responsibilities

• Build and maintain scalable infrastructure and pipelines for model deployment and production inference (supporting model enablement rather than model development).
• Collaborate with Data Scientists and Product Teams to turn model outputs into production-ready services.
• Improve scalability, performance, and reliability across inference workflows.
• Design and implement data pipelines that support machine learning enablement workflows.
• Participate in code reviews to support quality and alignment with engineering best practices.
• Apply established software design patterns and contribute to architectural discussions.
• Evaluate and implement practical improvements to ML enablement processes.
• Contribute to an AI Development Platform that enables adoption of AI capabilities across the enterprise.
• 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.
• Make implementation decisions that balance cost, time, and technical capability.
• Collaborate with senior team members, learn from them, and share knowledge with peers.
• Contribute to assigned workstreams to ensure successful and timely delivery.
• Work independently on well-defined problems, escalating ambiguous or high-impact decisions as needed.

Requirements

• 3 to 5 years of experience in a machine learning engineering or related role.
• Strong programming skills in Python, with additional languages considered a plus.
• Experience building scalable data processing and applications that enable machine learning.
• 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.
• Strong analytical and problem-solving skills, with the ability to adapt as technologies evolve.
• Good communication skills to collaborate with data scientists, engineers, and stakeholders.

Key Technologies

• 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.
• Annual cash bonus opportunity.
• Health, Dental, and Vision benefits starting Day-One.
• 5% matching 401(k).
• 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.