$ cat jobs/senior-deep-learning-engineer-sumersports-llc-015593923d2f.json
Senior Deep Learning Engineer
SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform empowers teams with insights and tools to make informed decisions within salary cap constraints. The platform also serves the NCAA, offering insights around the transfer portal and more. What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football. Position Summary As a Senior Deep Learning Engineer on the Football Modeling side, you'll work closely with our research team on player tracking data, evaluation, and forecasting models. You'll be a senior voice in the room on modeling decisions. We believe good research is less about having the perfect idea and more about building a rigorous system for testing ideas. Ideas are plentiful. The real work is designing experiments, learning quickly, and following the evidence. Responsibilities Contribute to entire modeling lifecycle including training, testing, and evaluation. Take one or two flagship modeling threads and drive them from problem definition through evaluation to production. Be a senior peer to the existing research team. Push back, share judgment, build consensus on what to try next. Work with football subject-matter experts on feature design and label discipline. Mentor mid-level engineers. Build out the experimentation harness so the team can run more ideas faster. Qualifications Track record shipping deep-learning models at scale. Transformer, sequence, or multimodal architectures. Strong fluency with PyTorch and PyTorch Lightning, distributed training, attention variants,
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