Senior Machine Learning Operations Engineer
About Veho
Veho’s mission is to power the future of commerce by making shopping, shipping and returns seamless for everyone. We are building a modern, end-to-end logistics infrastructure designed entirely for the ever-evolving needs of ecommerce brands and everyday consumers. Powered by next-generation technology and a vertically integrated supply chain, Veho gives brands and their customers unprecedented control over their deliveries and removes the pain from the ecommerce post-purchase experience. We make delivery the 'extension of the brand' and leverage it to create deeper loyalty and trust between brands and their customers, driving customer retention and lifetime value.
Our rapidly growing client list includes leading consumer brands like Hello Fresh, Zara, Macy’s, Sephora, and more. To truly build an iconic company, we strongly believe that our people and values must be aligned with our mission. As such, we take pride in our championship team, merit-based culture. We seek team players who want to compete, win, make an impact and build a legacy, and we reward performance and impact players with generous equity and incredible career growth opportunities.
About The Role
As a Senior Machine Learning Operations Engineer you’ll be embedded in a team of talented data scientists and software engineers to create sophisticated models that answer hard questions centered around improving our logistics network and user experiences. This role bridges between ML platform work and building on top of our platforms to create new models. You’ll create the infrastructure and tooling necessary to deploy, monitor, and scale our machine learning models in production. In close collaboration with data scientists you’ll own our production models, ensuring optimal performance and responding to production incidents.
- Create reliable, efficient, and scalable infrastructure for our AI/ML capabilities
- Create robust data pipelines to feed analyses and models
- Enable forecasting, network orchestration, and live pricing systems
- Ensure data quality and data integrity through best practices in data integration
- Build out robust feature stores, model orchestration tooling, experimentation tooling, model performance monitoring
- Create standards and templates for model development and deployment across all Data Science teams
What You’ll Do
Become a key member of the Data Science team by:
- Building reliable, efficient, and scalable infrastructure for our AI/ML capabilities
- Creating robust data pipelines to feed analyses and models
- Enabling forecasting, network orchestration, and live pricing systems
- Ensuring data quality and data integrity through best practices in data integration
- Building out robust feature stores, model orchestration tooling, experimentation tooling, model performance monitoring
- Creating standards and templates for model development and deployment across all Data Science teams
What You Bring
- Bachelor’s Degree plus at least 3 years of experience in machine learning engineering, or Master’s Degree plus at least 2 years in machine learning engineering
- This experience should include:
- Developing and optimizing MLOps pipelines for speed, reliability, and observability
- Utilizing statistical modeling or machine learning techniques to solve business problems
- Strong proficiency in Python and SQL
- Hands-on experience with open-source languages and tooling for large-scale ML (e.g., Ray, Flink, Feast)
- Utilizing cloud-based (AWS Preferred) data engineering and data science tools
- Experience building ML systems in Startups is a plus
- Experience with DS/ML in Logistics/Supply Chain is a plus
Pay
TBD
Schedule
N/A
Benefits
N/A