Job Details

*Lead Systems Architect: Machine Learning & Operational Intelligence*

Check all associated application documentation thoroughly before clicking on the apply button at the bottom of this description.

*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. xhqgsiq 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