Full-Time

Software Engineer

ML Platform

Posted on 6/3/2025

Penn Interactive

Penn Interactive

201-500 employees

Develops online sportsbooks and casino games

Compensation Overview

$103k - $161.7k/yr

+ Commission + Bonus

Philadelphia, PA, USA

Remote

Category
Software Engineering (2)
,
Required Skills
LLM
Kubernetes
Microsoft Azure
Python
Airflow
Tensorflow
Git
Pytorch
SQL
Docker
AWS
Terraform
Confluence
Google Cloud Platform
Requirements
  • Experience: 2+ years of experience in machine learning, data, or backend software engineering
  • Proficiency in Python and SQL
  • Familiarity with cloud platforms such as Google Cloud Platform, Amazon Web Services, or Microsoft Azure
  • Hands-on experience with ML model deployment, CI/CD pipelines, infrastructure as code tools such as Terraform, containerization technologies such as Docker and Kubernetes, and orchestration tools such as Dagster, Airflow, Kubeflow, or similar
  • Experience with model packaging and serving technologies such as TensorFlow, PyTorch, MLflow, Vertex AI, or AWS SageMaker
  • Solid communication skills and a desire to work cross-functionally with data scientists, ML engineers, and platform teams
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field
  • Nice to have: Experience building real-time personalization or recommendation systems at scale
  • Nice to have: Familiarity with monitoring, observability, and alerting tools for ML systems
  • Nice to have: Exposure to working with or deploying large language models in production
Responsibilities
  • Build and optimize end-to-end machine learning pipelines from data ingestion to deployment
  • Work closely with Product, Marketing, and Operations teams to align ML solutions with business goals
  • Improve our ML platform and deploy infrastructure using MLOps best practices
  • Evaluate and integrate new tools, models, and frameworks to enhance scalability and performance
  • Clearly communicate technical concepts to both technical and non-technical stakeholders
  • Document your systems and workflows using Git, Confluence, and related tools
  • Develop Personalized Recommendation Engines to connect users with the content, games, and promotions they will love
  • Implement an Experimentation Framework to guide data-driven decision-making by providing foundations for AB testing and experimentation
  • Implement Dynamic Personalization to create real-time, ML-driven decisions that improve user journeys
  • Scale our ML platform using the latest tools and best practices (GCP, Kubernetes, PyTorch, Dagster, and more)
Desired Qualifications
  • Experience building real-time personalization or recommendation systems at scale
  • Familiarity with monitoring, observability, and alerting tools for ML systems
  • Exposure to working with or deploying large language models in production

Penn Interactive specializes in developing online sportsbooks, casinos, and free-to-play gaming experiences, utilizing cutting-edge technologies to deliver immersive sports betting experiences and enhance the overall gaming experience. The company leverages advanced technologies to provide a seamless and engaging gaming experience, including innovative features for sports betting and casino gaming.

Company Size

201-500

Company Stage

N/A

Total Funding

N/A

Headquarters

Philadelphia, Pennsylvania

Founded

2015

Growth & Insights

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
INACTIVE