Senior Machine Learning Engineer

Quick Facts

• Role: Senior Machine Learning Engineer

Description

Join a team of machine learning engineers building, deploying, and scaling AI science models. As a Senior engineer, you deliver durable solutions, lead complex ML technical work, and help improve team processes.

Responsibilities

• Lead technical design for complex ML features and systems; make architectural decisions; document reusable patterns

• Build durable examples and drive best-practices adoption, including testing and observability

• Debug complex, ambiguous technical issues and coordinate for needed knowledge/resources

• Stay current with modern AI-assisted development practices; evaluate and adopt new technologies

• Design and refine ML features and pipelines across the ML lifecycle with data scientists

• Provide accurate project estimates considering technical risks, capacity, and quality of AI-generated code

• Remove roadblocks through cross-functional influence while maintaining quality standards

• Own delivery of major features/projects, manage risks, and keep stakeholders informed

• Run and interpret A/B tests and statistical analyses to assess model/feature impact

• Collect and analyze customer feedback and product data to inform product direction

• Define success metrics, track adoption and impact, and drive post-launch iterations

• Share feedback for team growth; resolve ambiguities; document what works

• Collaborate cross-functionally with product managers, data/AI scientists, and product engineers

Requirements

• BS, MS, or PhD in Computer Science or related field, or equivalent practical experience

• 5+ years of experience

• Knowledge of data science/AI tools and frameworks: Python, Scikit-learn, NLTK, NumPy, Pandas, TensorFlow, Keras, R, Spark

• Solid understanding of ML techniques (classification, regression, clustering) and ML principles

• Computer science fundamentals: data structures, algorithms, performance complexity, computer architecture

• Software engineering fundamentals: version control (Git/GitHub) and ability to write production-ready code

• Experience deploying highly scalable software for millions+ users; GPU acceleration (CUDA, cuDNN) and cloud experience (AWS, GCP)

• Strong oral and written communication skills

Benefits

• Competitive compensation with pay-for-performance rewards approach

• Eligible for cash bonus, equity rewards, and benefits per applicable plans