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