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