ML Engineer / Data Scientist

San Francisco • $160k - $220k • 0.3% - 0.4%

E Pluribus Fusion


Role Location

  • San Francisco

Compensation

  • $160k - $220k
  • 0.3% - 0.4%

Employees

11 - 25 people

Address

1880 Century Park E Ste 900
Los Angeles, CA, 90067-1610, US

Tech Stack

  • Go
  • Rust
  • ML
  • AWS
  • TypeScript
  • Python
  • R

Role Description

Our Mission

We are building 3D data models of sporting events in real-time via image recognition and ultra-wideband tracking.

Our Values

  • Work hard, have fun, dream big: we want to change the way sports is consumed.
  • Best idea wins: the team uses the best idea regardless of seniority.
  • Thirst for knowledge and improvement: never stop learning and finding better ways to solve problems.
  • Be a self-aware team player: recognize your role in the team to achieve our goals and help others.
  • Teams are organized according to scrum/agile principles: engineers are given a chance to focus on the task at hand without undue distraction.
  • Weekly sprints: we make small, achievable goals and strive to complete them.

How You Can Help

  • Build out our ML data pipeline.
  • Study and transform data science prototypes.
  • Design machine learning systems.
  • Implement working models based on published papers.
  • Research and implement appropriate ML algorithms and tools.
  • Run machine learning tests and experiments.
  • Perform statistical analysis and fine-tuning using test results.
  • Train and retrain systems when necessary.
  • Extend existing ML libraries and frameworks.
  • Coordinate a team image labelers.

Skills

  • You are passionate about sports data.
  • Experience with data science languages such as Python and R.
  • Deep knowledge of math, probability, statistics and algorithms.
  • Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).
  • Ability to take existing models and convert them to other frameworks, such as PyTorch to CoreML, Tensorflow, or ONNX.
  • Deep knowledge of neural nets and when to use each, i.e. MLPs, CNNs, and RNNs.
  • Familiarity with cloud infrastructure providers such as AWS, Azure, or GCP.
  • Familiarity with video codes such as H.264 and HEVC (H.265).

About E Pluribus Fusion

With our real-time 3D tracking technology, we create data models for live predictive analytics. This enables new types of fantasy sports games that are more engaging for fans—both in the stadium and at home.

We also create interactive AR experiences for fans that improve the engagement with teams and players. These experiences can be personalized and easily integrate with social media.

With unprecedented access to sporting events, we aim to partner with sports leagues around the world to implement this technology. With hands-on R&D at live events, we are developing edge hardware that streams to our cloud-based ML systems.

Company Culture

We value keeping technical debt low, striving for excellence, and learning and growing as engineers.

Interested in this role?
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