Sr. ML Engineer / ML Architect
New York, NY, 10001
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
- 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
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