Senior Machine Learning Engineer

Role Overview

• 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
• Balance cost, time, and technical capabilities when implementing solutions that meet stakeholder requirements
• 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.

Tech Stack

• AWS
• Cloud
• Docker
• EC2
• NoSQL
• Python
• SQL

Benefits

• Competitive Salary
• Opportunity for annual cash bonus
• 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