About the job

This role requires you to design and implement end-to-end Machine Learning (ML) models and systems to drive business impact by creatively solving cross-disciplinary problems at the boundary of what's possible. You collaborate closely with our static code analysis and runtime monitoring teams to detect data flows within our customers' products and let privacy teams answer their most pressing questions: What personal data is being processed by my organization? About whom? Where? When? Why? Given you are constructing the foundation on which our global data infrastructure will be built, you need to pay close attention to detail and maintain a forward-thinking outlook as well as scrappiness for the present needs. You thrive in a fast-paced, iterative, but heavily test-driven development environment, with full ownership to design features from scratch to impact the business and the accountability that comes along.

Responsibilities:

  • Creatively apply machine learning to cross-disciplinary problems that have never been solved before
  • Collaborate closely with our source code analysis and runtime monitoring engineering teams to build the core of a unique product that will reshape an entire industry
  • Architect production-grade systems to balance scrappiness for the current needs with a forward-thinking outlook to improve and scale our infrastructure
  • Follow and promote software engineering and machine learning best practices across the organization; keep up to date with the state of the art developments in ML/NLP applications to program static/runtime analysis, and MLOps
  • Shape the direction of machine learning at Relyance and build a cohesive team culture of ownership, growth, transparency, and customer focus

You are a good fit if you:

  • Have a track record of delivering production-grade ML models and systems
  • Have experience with at least one of static code analysis or runtime monitoring
  • Have strong software engineering skills, and set examples by writing clear, concise, and maintainable code considering design principles and applying sound testing practices
  • Are comfortable with Python, and have experience with ML/NLP tools and libraries such as scikit-learn, PyTorch, TensorFlow, spaCy, Hugging Face, etc.
  • Have a systematic and goal-directed approach to project management; are comfortable dealing with ambiguity and ruthlessly prioritizing and managing your time with a sense of urgency
  • Thrive in a self-directed environment with full ownership to design features from scratch to impact the business and the accountability that comes along
  • Are deeply curious, proactive about continuous improvement, and excited about learning at breakneck speed in a fast-growth environment; are eager to candidly and directly give and receive feedback to improve together as a team
  • Are customer and mission-driven, motivated by bringing the most value as possible to users and shaping an industry from the ground up
  • Are the ultimate team player: collaborate effectively with others, consistently make time to help your teammates, and are ego-less in the search for the best ideas

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