Vacancy expired!
- Comfortable with math, statistics, systems design and coding to the extent necessary to tackle industrial machine learning and data science challenges. A PhD in a quantitative field (computer science, statistics, mathematics, operations research, science, engineering, etc.), is preferred and is a good indicator of sufficient preparation but is not strictly required: what you can do (or quickly learn to do) is more important.
- Exposure to a minimum introductory level treatment of the core concepts and methods in machine learning, and some applied experience deploying those methods towards solving data science problems.
- Familiarity with current machine learning development ecosystems (Python, PyTorch / TensorFlow, Git, etc.)
- Comfortable collaborating in a dynamic, cross-functional team: you know how to listen, ask questions, build consensus, advocate (with data), and share success. You are willing to assume leadership and ownership over technological, business, or team responsibilities.
- Strong written and verbal communication skills: you can communicate clearly and effectively with peers and non-technical stakeholders alike. You can explain your plan for solving a business problem clearly and document your work concisely.
- Working knowledge of advanced machine learning theory and methods, whether through experience or (graduate) coursework.
- Direct experience applying ML/AI in a business environment, and experience distilling high-level business challenges down to concrete modeling problems.
- Familiarity with bash scripting, relational databases.
- Familiarity with CI/CD tools and procedures, containerization, and horizontal scaling in latency sensitive ML-centric / production inference settings.
- Research publication track-record.
- Frame, design and execute your own solutions to modeling problems that will improve user experience and/or optimize key metrics important to the business.
- Conduct experiments and engage in rapid-prototyping of ideas, making creative use of the data and resources at your disposal.
- Implement designs in a stable, maintainable, and scalable production-ready form.
- Extract, process and leverage massive amounts of data to drive successful projects.
- Engage in group problem-solving, and collaborative team efforts.
- Communicate and share results in a clear and concise manner.
Vacancy expired!