INACTIVE
Full-Time
Machine Learning Engineer
Posted on 1/13/2023
Offers approachable sports contests and games online
Compensation Overview
$100,000 - $170,000
Junior, Mid, Senior
Remote + 1 more
Required Skills
Python
Data Science
Tensorflow
R
Keras
Pytorch
iOS/Swift
Natural Language Processing (NLP)
Computer Vision
Product Design
Data Analysis
Requirements
- BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related academic/work experience
- 3+ years of experience building and deploying ML/DL models or systems
- Industry experience of applying scientific methods to solve real-world problems on consumer scale data
- Strong analytical and problem-solving skills. You thrive in ambiguous environments, get excited about finding solutions to complex problems, and then execute on them
- Ability to work autonomously and lead initiatives across multiple product areas and communicate findings with leadership and product teams
- Proven ML and software engineering skills across languages including Python, R, Swift etc
- Experience with ML software tools and libraries (e.g., Scikit-learn, Keras, PyTorch, Huggingface, Haystack, Fastai, TensorFlow, Nvidia, Nbdev.)
- Experience with MLOps pipelines
- MS, PhD in Computer Science or related field with research in machine learning
- Familiarity with large-scale data processing and distributed systems
- Experience with one or more of the following: statistics, causal inference, natural language processing, computer vision, bayesian reasoning, recommendation systems, search and ranking, learning from semistructured data, graph learning, reinforcement or active learning, ML software systems, machine learning on mobile devices
Responsibilities
- Design, explore, build, evaluate, deploy and iterate on large scale ML systems
- Perform model explainability analysis
- Evaluate the performance of ML systems against business objectives
- Work with large scale data systems
- Set up and refine the ML tech stack, and build systems that help Underdog personalize their users' experience
- Work with Product, Design, Infrastructure, and Frontend teams to bring your models, and features to life
- Contribute across the data science and ML development stack: ideation, opportunity sizing, prototyping, testing, and deployment
- Data Scientists will analyze data used by both our Sportsbook and Fantasy applications
Underdog Fantasy, a rapidly expanding sports company, is distinguished by its commitment to delivering enjoyable and accessible contests and games, crafted by a team of seasoned industry professionals. The company's competitive edge lies in its user-centric approach, striving to enhance the overall experience for its passionate user base. As a leader in its industry, Underdog Fantasy is reshaping the sports gaming landscape with its unique blend of fun and approachability.
Company Stage
Series B
Total Funding
$123.4M
Headquarters
Brooklyn, New York
Founded
2020
Growth & Insights
Headcount
6 month growth
↑ 16%1 year growth
↑ 91%2 year growth
↑ 348%INACTIVE