Senior Machine Learning Engineer developing AI solutions for IDEXX's Data & AI Center of Excellence. Designing and implementing machine learning models and systems while collaborating with cross-functional teams.
Responsibilities
Develop and implement scalable software and infrastructure solutions in support of model training, development, and production inference.
Collaborate with Product Teams and Data Scientists to analyze and clarify requirements, translating them into robust technical solutions.
Contribute to the scalability, performance, and reliability of applications, training, and inference workflows.
Design and implement data pipelines to support machine learning workflows.
Participate in code reviews to ensure high-quality code and adherence to best practices in machine learning and software engineering.
Apply software design patterns and contribute to architectural discussions.
Demonstrate initiative by identifying and applying innovative approaches to a variety of ML engineering challenges.
Contribute to the design and development of an AI Development Platform, supporting the adoption of AI capabilities throughout the enterprise.
Work closely with Data Engineering and DevOps to build robust processing workflows and pipelines.
Partner with technical product management and engineering teams to identify reusable datasets, design patterns, components, libraries, and infrastructure that optimize costs and enable cross-functional solutions.
Share knowledge and provide technical guidance to junior team members, contributing to a culture of learning and continuous improvement.
Contribute to team initiatives and drive assigned workstreams to successful and timely completion.
Operate with a high degree of independence on well-defined problems while escalating ambiguous or high-impact decisions appropriately.
Requirements
Strong programming skills in Python, with proficiency in additional languages.
Solid experience designing and building scalable data processing and ML applications.
Sound software engineering practices, including test-driven development and CI/CD.
Strong understanding of AI/ML concepts and hands-on experience deploying models in production environments.
Familiarity with ML tech stacks such as Databricks, Delta Tables, AWS (EC2, S3, SageMaker), and containerization tools like Docker.
Working knowledge of data engineering (SQL, NoSQL, Big Data), cloud architecture, Agile methodologies, and MLOps/ModelOps practices.
Experience with DevOps practices and designing resilient, scalable data systems.
Strong analytical and problem-solving skills, with the ability to adapt to evolving technologies.
Good communication skills to collaborate effectively with data scientists, engineers, and stakeholders.
Benefits
Health / Dental / Vision Benefits
Day-One 5% matching 401k
Additional benefits including but not limited to financial support, pet insurance, mental health resources, volunteer paid days off, and much more
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