Senior Machine Learning Engineer
Posted on 12/8/2023
INACTIVE
FanDuel

1,001-5,000 employees

Fantasy sports and online U.S. sportsbook
Company Overview
Fanduel is on a mission to make sports more exciting. The company provides a daily fantasy sports platform with a range of game types for players with a guaranteed prize pool for the winners.
Data & Analytics

Company Stage

N/A

Total Funding

$4.6B

Founded

2009

Headquarters

New York, New York

Growth & Insights
Headcount

6 month growth

9%

1 year growth

22%

2 year growth

79%
Locations
Atlanta, GA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Microsoft Azure
Python
Apache Flink
Tensorflow
Data Structures & Algorithms
Keras
Pytorch
Apache Spark
Apache Kafka
Java
Tableau
AWS
Unity
Google Cloud Platform
CategoriesNew
AI & Machine Learning
Software Engineering
Requirements
  • 5+ years of relevant experience developing code in one or more core programming languages (Python, Java, etc.)
  • 1+ Years of experience in deploying ML models under the constraints of scalability, correctness, and maintainability
  • Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, etc.)
  • 3+ Years of experience designing and building various software architecture
  • Deep understanding and knowledge of data structures and software engineering principles
  • 2+ Years of experience demonstrating technical leadership working with teams, owning projects, defining, and setting technical direction for projects
  • Experience with one or more relevant tools (Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis)
  • Ability to share findings in easy to consume formats, whether that is through dashboards or data modeling
  • Conduct regular design process reviews and ensure development standards within the team
  • Working with leadership to drive adoption of ML solutions to product engineering teams
  • Experience working in a cloud environment such as AWS, GCP, Azure
  • Experience with Databricks is a plus, their unity catalog, another plus
  • Designing and building data pipelines for production level ML infrastructure
  • Motivate junior engineers on best practices and latest industry design patterns
Responsibilities
  • Building multi-layer serving architectures for ML models
  • Business intelligence tools (e.g., Tableau, Knime, Looker)
  • Data security and privacy (e.g. GDPR, CPP)
  • Data governance and data testing frameworks
  • Continuous integration and delivery of production data products
  • Advance your career within well-defined, skill-based tracks, either as an individual contributor or as a manager – both providing equal opportunities for compensation and advancement
  • Apply your experience and intellect as part of an autonomous team with end-to-end ownership of key components of our data architecture
  • Serve as a mentor to more junior engineers not only in cultivating craftsmanship but also in achieving operational excellence – system reliability, automation, data quality, and cost-efficiency
Desired Qualifications
  • Experience with Databricks
  • Experience with ML solutions in product engineering teams
  • Experience with data security and privacy regulations (e.g. GDPR, CPP)
  • Experience with cloud environments such as AWS, GCP, Azure