About the position
Grubhub, part of Wonder Group Inc, is all about connecting hungry diners with our network of over 375,000 merchants nationwide. Innovative technology, user-friendly platforms and streamlined delivery capabilities set us apart and make us an industry leader in the world of online food ordering. When you join our team, you become part of a community that works together to innovate, solve problems, grow, work hard and have a ton of fun in the process! As a matter of company policy, Grubhub does not sponsor applicants for employment visa status for this role. The Data Science Solutions team is a mix of data scientists and software engineers dedicated to building robust experimentation, machine learning and decision modeling solutions for teams across Grubhub. The solutions built by this team help drive Grubhub products such as delivery estimation, dispatch decisions, driver scheduling, etc., as well as provide a platform for teams to manage experiments and automate the analysis of those experiments.
Responsibilities
- Assist in the design and implementation of experimentation, MLOps and decision modeling pipelines that enable our data scientists to iterate on and deploy changes efficiently.
- Help implement monitoring frameworks to maintain system observability and quickly address any issues, contributing to minimizing SEV incidents.
- Contribute to platform improvements by exploring tools and integrations that enhance the data science workflow and ensure smooth integration with the GrubHub platform.
- Collaborate with data scientists to implement best practices in coding, testing, and version control, contributing to the overall quality and reliability of our codebase.
- Assist in establishing processes for better data lineage, documentation, and ownership across datasets, reducing inconsistencies and promoting team autonomy.
- Participate in the development of systems for data versioning, model management, and deployment strategies, ensuring models are manageable and easy to deploy.
Requirements
- 3+ years in software engineering with a focus on MLOps, Python, and cloud-based environments (AWS preferred).
- Proven experience in building and maintaining CI/CD pipelines, managing monorepos, and scaling machine learning models in production.
- Proficiency in Python, containerization, orchestration tools, and experience with data versioning and model management tools.
- Additional experience in Java is a plus.
- Front-end experience with Flask or React is a plus.
- Experience or knowledge of training, deploying and monitoring ML models is a plus.
- Ability to address challenges related to system integration, data consistency, and infrastructure.
- Experience with distributed systems and microservices architecture is a plus.
- Strong communication skills, with the ability to work closely with data scientists, product managers, and other engineers.
- Passion for staying up-to-date with the latest trends in MLOps, machine learning, and software engineering, with a drive to continuously improve and innovate.
Nice-to-haves
- Experience with distributed systems and microservices architecture.
- Knowledge of training, deploying and monitoring ML models.
Benefits
- Generous PTO.
- Excellent medical, dental and vision benefits.
- 401k matching.
- Employee network groups.
- Paid parental leave.
- Weekly Grubhub credit for free meals.
- Paid time off to support social causes.
