Senior Machine Learning Operations Engineer
About the role
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 evolving needs of e-commerce 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 e-commerce 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.
Veho is rapidly growing, with clients including leading consumer brands like Hello Fresh, Zara, Macy's, Sephora, and more. As a company, we strongly believe in aligning our people and values with our mission. We take pride in our championship team, merit-based culture, and offer generous equity and incredible career growth opportunities to performance and impact players.
Responsibilities
- Build 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
Requirements
- 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)
- Working with Data Warehouses (e.g., Redshift, Databricks, Snowflake)
- 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
Qualifications
- 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
Skills
- Expertise in machine learning operations engineering
- Collaboration with data scientists to create and optimize machine learning models
- Strong proficiency in Python and SQL
- Experience with cloud-based data engineering and data science tools
- Experience building ML systems in startups
- Experience with DS/ML in logistics/supply chain
Benefits
- Generous equity packages
- Incredible career growth opportunities
Pay
Competitive compensation package based on experience and qualifications.
Schedule
Full-time position.