Lead Systems Architect

Lead Systems Architect: Machine Learning & Operational Intelligence

The Mission

CASS Inc. is a growth-oriented vertical manufacturer dedicated to the circular economy. We specialize in transforming end-of-life materials into high-performance aluminum alloys. Our objective is to lead the industry through a culture of excellence, where sophisticated technical innovation meets a deep-rooted commitment to sustainable industrial practices.

We are seeking a Lead Systems Architect to build and own our data-to-intelligence pipeline. This is a "ground-up" opportunity for a specialist who understands that true Machine Learning (ML) success begins with rigorous Data Analysis and ends with practical, real-world operational impact.

The Role: Foundation, Analysis, & Innovation

You will be the primary architect of our digital evolution. We believe that the most significant innovations occur when high-level data science is applied to complex physical processes. Your goal is to move beyond static reporting and develop a dynamic, predictive environment.

Key Responsibilities

• Establish the Data Foundation: Build and own a centralized data layer that integrates disparate streams—from legacy ERP systems to real-time IoT sensors on the foundry floor.
• Deep Data Analysis: Perform high-level diagnostic and exploratory analysis to identify hidden inefficiencies in our production cycles, energy consumption, and material yields.
• Deploy Applied Machine Learning: Design and implement production-grade ML models focused on:
• Process Optimization: Enhancing furnace efficiency and reducing resource intensity.
• Predictive Forecasting: Building models to navigate commodity market volatility and supply chain logistics.
• Quality Engineering: Using computer vision or sensor data to ensure uncompromising quality standards.
• Drive a Culture of Innovation: Act as a technical bridge, collaborating with operations teams to translate complex industrial challenges into elegant, scalable software solutions.

The Ideal Candidate

• The Technical Core: Mastery of Python and SQL. Deep experience with the modern ML stack (e.g., Scikit-learn, PyTorch, or XGBoost) and the data engineering required to support it (ETL/ELT).
• The Analytical Mind: You don't just "run models"—you interrogate data. You have a proven ability to find the "signal" in noisy, unstructured industrial datasets.
• Builder Mentality: You are energized by "Greenfield" projects. You are comfortable choosing the right tools and setting the standard for how code is written and deployed.
• Integrity & Excellence: You hold your work to the highest standards, ensuring that our technical systems are as robust and reliable as the alloys we produce.

Our Culture & Sustainable Impact

• Data-Driven Stewardship: We use innovation to minimize our environmental footprint, proving that industrial growth and sustainable practices are mutually inclusive.
• Commitment to Community: We are a responsible member of the local communities where we operate. Your work in optimizing our efficiency directly contributes to the well-being and environmental health of our neighbors.
• Continuous Evolution: We foster an environment that rewards curiosity and rewards those who look for a "better way" to solve age-old industrial problems.

Pay: From $160,000.00 per year

Benefits:

• 401(k)
• Dental insurance
• Paid time off

Application Question(s):

• Tell me about something you built from the ground up and what would you do differently now?
• How do you balance model complexity with real-world reliability on the floor?
• Describe an ML model you deployed into production. What changed after deployment?
• If furnace efficiency dropped 8% over two weeks, how would you investigate the root cause?
• Walk me through how you would design a centralized data layer for a manufacturing environment with ERP data, sensor data, and manual logs. Where do you start?
• As part of our standard hiring process, all candidates complete a background check and onsite hair follicle drug screening. Are you able to meet this requirement?
• This is a fully onsite role. Are you able to work onsite as required?

Ability to Commute:

• Oakland, CA 94607 (Required)

Ability to Relocate:

• Oakland, CA 94607: Relocate before starting work (Required)

Work Location: In person