Senior Machine Learning Operations Engineer

Veho · Boston, MA · Yesterday

HybridFull-time

About the role

This role is embedded in a team of talented data scientists and software engineers to create sophisticated models that improve Veho's logistics network and user experiences. It bridges between ML platform work and building on top of Veho's platforms to create new models. The Senior Machine Learning Operations Engineer will create the infrastructure and tooling necessary to deploy, monitor, and scale machine learning models in production. They will also ensure optimal performance and respond to production incidents.

Responsibilities

Create reliable, efficient, and scalable infrastructure for 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, and 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
Experience developing and optimizing MLOps pipelines for speed, reliability, and observability
Experience 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)
Experience working with Data Warehouses (e.g., Redshift, Databricks, Snowflake)
Experience building ML systems in Startups is a plus
Experience with DS/ML in Logistics/Supply Chain is a plus

Qualifications

Expertise in their craft, creating high-quality ML infrastructure and delivering impactful machine learning models to stakeholders
Works in close collaboration with the Data Science team and keeps business value at the center of their work
Has a bias for action, balancing short-term impact with long-term vision
Applies ML/MLOPS knowledge to suggest new patterns, tools, and approaches to improve the team's models

Skills

Python
SQL
Open-source languages and tooling for large-scale ML (e.g., Ray, Flink, Feast)
Cloud-based data engineering and data science tools (AWS preferred)
Data Warehouses (e.g., Redshift, Databricks, Snowflake)

Benefits

Generous equity
Incredible career growth opportunities