招聘
Do you want to change the world? Ford Motor Company has endured and thrived for more than 118 years by reimagining how things are built. Today, Ford is leading a once-in-a-generation transformation in manufacturing — scaling EVs, integrating humanoid robotics, additive manufacturing, AI vision, and digital platforms into one seamless operating system: the Ford Production System (FPS/FPS+) that operates within the FAST framework.
Ford Motor Company is undergoing a historic industrial shift—from building great vehicles to building great systems that scale across them. The Advanced Industrial Technology & Platforms (AITP) organization was created to operationalize that shift. Our job is not to deploy isolated tools; it is to build a system that learns from factory truth, transforms it into scalable platforms, and turns those platforms into enterprise business value.
Advanced Industrial Technology and Platforms (ATP) — a new, centralized organization designed to position Ford to lead industrial innovation. This team will accelerate our digital evolution and manufacturing excellence – advancing the modernization of our Ford Manufacturing operations with cutting-edge technology. As part of Ford Manufacturing, ATP is designed to integrate directly into our manufacturing sites, partner across teams (GME, safety, etc.) and drive innovation from initial idea to full implementation. ATP is led by Managing Director Yung Fung, reporting to Ford Chief Manufacturing Officer Bryce Currie.
This new structure includes four vertical business units — focused on specific technology stacks —and four horizontals — shared services designed to ensure scale, deployment and operational consistency.
As part of AITP organization, one of the business verticals is Sight, that will build end-to-end business around AI/ML anomaly detection products, with image (Sight) and para metric data (Sense).
This transformation requires leaders who can compress readiness cycles, integrate next-generation platforms, and deliver breakthroughs that set new global standards in industrial AI/ML anomaly detection products.
Focus: Technical Architecture, Delivery & Team Leadership
The Opportunity
As the Sense Engineering Manager, you are the "Chief Architect" of the parametric detection suite. Your mission is to build robust, scalable software and hardware interfaces that can handle the massive data throughput of Ford’s global manufacturing footprint. You will lead the engineering team to move Sense products from "Concept" to "MRL 9" maturity.
The Position
You will lead a team of software, data, and systems engineers. You are responsible for the technical integrity of the Sense products and their seamless integration into Ford’s CoreOS and digital infrastructure. You will report to Sense Manager and work really close with Sight Vertical GM and Sense Product Manager.
Requires availability to travel across the globe when needed.
What You’ll Be Able to Do
Technical Decision Making: Own the architecture for Sense products, ensuring they are modular, externalizable, and "Build Once, Scale Everywhere" compliant.
Engineering Excellence: Direct the development of parametric models for CBM (Condition Based Maintenance), energy optimization, and in-line process tests.
Integration with CoreOS: Ensure all Sense products integrate with FPS+ and AIR (AITP Integrated Runtime) for real-time telemetry and issue tracking.
Lifecycle Management: Enforce rigorous technical gates (TRL/MRL) to ensure code quality, cybersecurity compliance, and industrial-grade reliability.
Mentor & Build: Grow the technical capabilities of the engineering team, fostering a culture of "Fix Fast, Future-Proof Ops."
Success in Role
Sense achieves TRL/MRL/IRL gates aligned to program milestones.
Zero-integration deployment of AI/ML anomaly detection products into FPS+ is demonstrated.
Pilot deployments compress from 18+ months to 90 days.
Robust and integrated SW/HW architecture and technology cross Sense Products
Sense transitions from incubation to scale (internal + external commercialization).
Value generated in quality improvement and cost savings in Mfg Plants with sense products
CoreDS serves as the standard ML & Data Platform for Sense Products
Functional & Technical Knowledge
Minimum Requirements
5+ years of experience in software engineering or systems architecture.
Experience leading engineering teams in the development of AI/ML-driven products.
Proficiency in cloud-to-edge architecture and industrial communication protocols (MQTT, OPC-UA).
Degree in Computer Science, Electrical Engineering, or a related technical field.
Expertise in modern programming languages (e.g., Python, C++, Java, or Go).
Experience with data pipeline tools and streaming architectures (e.g., Kafka).
Strong problem-solving skills and the ability to work in a fast-paced, "FAST AF" (Always First, Factory Ready) environment.
Strong experience in global collaboration
Preferred Requirements
Master’s/PhD in Software Engineering or Data Engineering and Eng/SW Development
10+ years of experience in software engineering or systems architecture.
Knowledge of automotive/manufacturing system integration (MES, GDPS 2.0, digital twins).
Automotive, aerospace, or other high-complexity manufacturing background.
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About Ford

Ford
PublicThe Ford Motor Company is an American multinational automobile manufacturer headquartered in Dearborn, Michigan, United States. It was founded by Henry Ford and incorporated on June 16, 1903.
10,001+
Employees
Spain
Headquarters
$48B
Valuation
Reviews
3.4
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.9
Management
2.3
45%
Recommend to a Friend
Pros
Good pay and benefits
Decent work-life balance options
Learning and advancement opportunities
Cons
Poor management and favoritism
Mandatory overtime and exhausting schedules
Limited growth opportunities
Salary Ranges
36 data points
Mid/L4
Senior/L5
Mid/L4 · ADAS Data Analytics Engineer
1 reports
$132,847
total / year
Base
$102,190
Stock
-
Bonus
-
$132,847
$132,847
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 40%
Neutral 40%
Negative 20%
Interview Process
1
Phone Screen
2
Technical Interview
3
Behavioral Interview
4
Final Round Interview
Common Questions
Behavioral
Technical
Assessment
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