Sr. ML Engineer / ML Architect

Job Title: Sr. ML Engineer / ML Architect Location-Type: Remote Start Date Is: June 16 Duration: (contract, perm, etc) 12 Month Contract Compensation Range: $90 - 110$/hr W2 Benefits: Eligible for Health, Dental, Vision, 401K Must be authorized to work in the U.S. This position is not eligible for sponsorship . Job Description: Our client is hiring a senior-level ML Engineer / ML Architect to help redesign and productize a highly business-critical internal system that supports sales account assignment and book-of-business management across 1,000 sales reps. The current system: • Handles extremely complex business logic and rule orchestration • Requires intensive compute and optimization processing • Has very little room for error due to direct downstream business impact • Creates operational escalations quickly when issues occur • Is currently owned heavily by one long-tenured math PhD engineer who needs to roll off the project after several years of ownership The team wants to: • Build a more scalable and configurable data product • Improve optimization performance and compute efficiency • Productize internal tooling for business users • Create real-time simulation/testing capabilities for sales operations users • Improve feature store architecture and pipeline design • Reduce infrastructure/storage bottlenecks and solver performance issues Core Responsibilities • Architect and optimize a large-scale internal data product supporting sales operations • Design scalable feature store infrastructure • Build and optimize ML/data pipelines • Improve solver performance and optimization efficiency • Design configurable systems for business users to run real-time simulations/mock runs • Help define and architect pipeline orchestration and system sequencing • Partner with existing software engineers and ML engineers on implementation • Improve compute efficiency and storage optimization • Build feedback loops between optimization systems and end-user configuration tooling • Help productize internal operational systems into more robust platforms Technical Environment: • Python-heavy environment • Some Java exposure preferred (Kafka ecosystem dependencies) • Snowflake/data warehouse environment • Kubernetes deployment infrastructure • Large-scale AWS infrastructure • Constraint programming / optimization solver systems • Heavy linear algebra and operations research concepts Technical Must-Haves: • Strong Python engineering background • Experience building large-scale data infrastructure and pipelines • Experience designing scalable backend/data systems • Strong systems architecture mindset • Experience optimizing compute-heavy systems • Exposure to optimization research / operations research / constraint programming • Experience working with solver-based systems or large optimization problems • Strong understanding of feature engineering and feature store architecture • Experience with web services and production infrastructure • Ability to think through data modeling and pipeline architecture • Strong performance optimization mindset Soft Skills: • Strong problem-solving ability • Systems thinking • Ability to architect ambiguous solutions • Comfortable operating in highly complex environments • Strong communication around technical tradeoffs • Strategic mindset beyond pure implementation • Ability to collaborate closely with existing engineering teams