Lucid’s mission is to inspire the adoption of sustainable energy by creating the most captivating luxury electric vehicles, centered around the human experience. Working at Lucid Motors means having a shared vision to power the future in revolutionary ways. Be part of a once-in-a-lifetime opportunity to transform the automotive industry. 

We are currently seeking a skilled Manager responsible for leading team of engineers of the ADAS / Autonomous Driving team for validation of software implementation of safety goals & reaction to faults. This position requires an experienced professional with a track record of successfully bringing new automotive (ADAS) systems into production. 

Our ideal candidate exhibits a can-do attitude and approaches his or her work with vigor and determination. Candidates will be expected to demonstrate excellence in their respective fields, to possess the ability to learn quickly and to strive for perfection. 

Your Role: 

• Manage, motivate & lead team of validation engineers who are responsible for testing & validating safety goals, and functional safety implementation related to ADAS/AD functions for urban, highway driving as well as safety features.  

• Contribute to system architecture development and the related validation tests on component, bench and/or vehicle level; Contribute to the timely delivery of testing of ADAS system related to safety confirmation 

• Be responsible for developing & executing test & validation plans for feature requirements related to safety and relevant regulations, data analysis and root causing while ensuring traceability to requirements 

• Align with related cross-functional technical teams such as Infotainment, functional safety, powertrain, cybersecurity, homologation, and ADAS/AD system & software development teams, feature owners and program managers on validation activities and overall execution of the project 

• Leverage state-of-the-art processes, tools for requirements & test plans, proving ground or on-road tests, data transfer & analysis;  also lead the development/adoption of new processes and tools in a highly interactive and collaborative environment; Mentor & support the team to develop test automation with industry tools such as CAPL scripting 

• Work with suppliers and internal teams to implement innovative solutions for vehicle testing & calibration approaches, fault injection tests etc. to optimize system test efficiency, cost and final product quality 

• Travel as necessary to execute safety goals validation & fault injection tests on vehicle at proving ground testing facilities and perform detail data analysis 

• Assist in definition and build-up of our benches, system buck & test vehicles etc. for all safety confirmation testing & validation of ADAS/AD features 

• Explore HIL and vehicle test approaches to optimize (sub-)system test, validation & calibration strategies in terms of efficiency, cost and final product quality 

• Work closely with component owners (Long and Short Range Radars, Front & Side Cameras & Lidar etc.) for the ADAS/AD driving functions, and contribute to safety related component requirements 

• Investigate root causes of component or system level failures; follow on and support resolution of issue tickets 

Expectations: 

• More than 10 years of automotive experience at OEM or Tier 1/2 ADAS/AD suppliers with at least 8 years of experience in developing & testing hardware/software systems related to safety critical automotive features for mass production, with preferably features involving longitudinal and lateral driving control and/or safety features, and with an understanding of automotive processes and workflows 

• Experience in leading & mentoring a team of highly skilled and talented engineers for automotive testing & validation activities  

• Strong experience in development and execution of validation test plans for safety goals and fault injection testing, with close collaboration with system engineering, software development and feature owner (product) teams; Experience debugging, testing, benchmarking, calibrating and bringing up complex vehicle safety critical features 

• Expert of few of the testing/validation tools & methods such as Vector (CANoe, CANape and CAPL), PeakCAN, DGPS, test benches and/or HILs; very strong understanding of CAN and Ethernet 

• Programming skills related to integration, testing, automation, results post-processing etc. (e.g. Python, C/C++, MatLab/Simulink) 

• Capability and creativity to successfully complete projects with unconventional ideas in highly constrained, innovative startup environments 

• Excellent communication skills (verbal and written) & ownership mindset 

Advantageous: 

• Proficiency with agile development tools and environments (Jira, Jama, …), and issue resolution system (such as JIRA) 

• Strong understanding of automotive functional safety standard and process (ISO 26262); and regulations (FMVSS, NITSA, GSR, NCAP) with test execution experience 

• Experience with test automation, with Diagnostics and UDS protocol 

• Experience with test benches, or HIL or system (vehicle) simulation 

• Broad experience with various vehicle systems, including mechanical, electrical and software components 

• Experience with project management, supplier management, team management and/or executing tasks in cross-functional team setup 

Requirements: 

• BS minimum in System Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, or similar and 10 years of engineering experience in the automotive industry 

OR 

• MS minimum in System Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, or similar and 8 years of engineering experience in the automotive industry 

We are currently seeking a highly skilled technical expert responsible for setting up virtual simulations with Hardware-in-Loop (HiL)/bench setups for system validation. This position requires a professional with experience in automotive industry standard Hardware-in-loop systems for complex electronic systems.  

As the successful candidate, you will join a world-class Autonomous Driving/ADAS team in Lucid. Candidates should be excellent engineers and organizers that have demonstrated the ability to learn quickly and work effectively in a fast-paced, rapidly changing environment. Our ideal candidate exhibits a can-do attitude and approaches his or her work with vigor and determination. 

Your Role: 

• Taking complete ownership of HIL and SIL setups & builds for ADAS/AD features validation with industry standard tools such as dSPACE, National Instrument or Applied Intuition tools. 

• Contribute to creating & updating the plant and control models & simulation setup; create & execute scenarios for features validation at ECU level, post-process results, generate report, discuss & present results to ADAS leadership for drawing appropriate conclusions. 

• Be responsible for developing necessary automation scripts to drive test cases that can be simultaneously executed in HIL and SIL solutions.  

• Correlate HIL and SIL results with actual vehicle test data as necessary.  

• Leverage state-of-the-art processes, validation tools, data transfer & analysis in a highly interactive and collaborative environment. 

• Facilitate and align with related cross-functional technical teams such as ADAS software development (motion planning, perception etc.), vehicle chassis, powertrain, infotainment for ADAS system level validation and development activities. 

• Work with suppliers as necessary and represent Lucid ADAS systems validation team. 

Expectations: 

• Deep understanding & experience developing HIL (Hardware-in-Loop) and SIL (Software in Loop) systems for ADAS/AD components and other complex vehicle ECUs from scratch and experience maintaining these systems as well as executing test cases for integration & validation. 

• Experience of industry standard HIL and SIL simulation tools such as dSpace or National Instruments; experience with CARLA, Ansys, Simens or other such tools is a plus. 

• Experience in integrating multiple sensors (Camera, Radar, Lidar and Ultrasonics) and/or safety critical vehicle ECUs into HIL setup.  

• Experience in various communication protocols such as CAN, Ethernet and LIN  

• Experience in working with complex automotive features for mass production 

• Working experience at automotive Tier 1/2 suppliers or OEMs, with an understanding of automotive processes and workflows 

• Programming skills related to simulation automation, results post-processing etc. (e.g. Python, C/C++, MatLab/Simulink) 

• Capability and creativity to successfully complete projects with unconventional ideas in highly constrained, innovative startup environments 

• Excellent communication skills (verbal and written) & ownership mindset 

Advantageous: 

• Experience in developing plant, control and vehicle dynamics models from scratch, model correlation and executing scenarios on cloud 

• Experience with ADAS/AD features such as ACC, Lane Keeping, AEB etc. 

• Understanding of Functional Safety (ISO 26262), SOTIF (ISO 21448), NCAP 

• Broad understanding of interactions between ADAS/AD and other mechanical, electrical and software components of vehicle 

• Experience with Vector tools: CANoe, CANape and CAPL 

• Proficiency with agile development tools and environments (Jira, Jama, …) 

Requirements: 

• BS minimum in System Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, or similar and 10+ years of engineering experience in the automotive industry 

OR 

• MS minimum in System Engineering, Mechanical Engineering, Electrical Engineering, Computer Science, or similar and 8+ years of engineering experience in the automotive industry 
• Minimum of 5+ years previous HIL experience in OEM or Tier-1 company

Role Responsibilities: • Requirements Analysis and Decomposition: Analyze and decompose system-level requirements into clear, actionable software tasks. Collaborate closely with system engineers to ensure alignment on ADAS feature requirements and system design integrity.

• SW integration: Develop and maintain integration pipeline for controls ADAS software to ensure automation of development and build pipelines.

• CI/CD infrastructure: Design, build, and maintain CI/CD infrastructure for L2/ L2++ ADAS projects, enabling scalable, automated build, integration, and validation pipelines to support rapid development and reliable software delivery. • Software Design and Architecture: Design robust, scalable software architectures for ADAS feature integration that meet functional, safety, and performance standards. • State Machine Implementation: Design and implement detailed state machine models for various ADAS features (active safety, driving, and parking). Validate correct logic through unit testing, SIL/HIL testing, and in-vehicle evaluation. • Cross-functional Collaboration: Partner with cross-functional teams including systems, product owner, validation, platform and controls to ensure seamless integration of ADAS features across the vehicle platform. • Documentation and Reporting: Maintain thorough documentation of software design, requirements traceability, unit test cases, and validation outcomes. Required Qualifications: • Bachelor's degree in Computer Science, Electrical Engineering, or a related field • 6+ years of experience in software development and software integration • Full-cycle software development experience with autonomous driving systems—from requirements to production deployment • Strong skills in C/C++/python and modeling environments such as MATLAB/Simulink

• Familiarity with CI/CD pipelines, build systems, and automated test frameworks • Strong debugging and problem-solving skills; comfortable working across embedded systems and real-time applications • Excellent communication skills and the ability to work effectively in a fast-moving, collaborative environment Preferred Qualifications: • Master’s degree with 6+ years experience, or Ph.D. with 3+ years experience • Hands-on experience with embedded platforms such as NVIDIA Xavier/Orin and Aurix; strong debugging and diagnostic skills across multicore architectures • Strong understanding of communication protocols (Ethernet) and tools like Vector CANape/CANoe

• Practical experience testing ADAS/AD features in both simulation and real-vehicle environments

• Deep knowledge in one or more areas of ADAS systems such as behavior planning, motion planning, or vehicle control • Experience with safety-critical systems and standards (e.g., ISO 26262, AUTOSAR)

Lucid Motors is seeking a Senior SQA and Test Infrastructure Development Engineer to help build the next generation of test, automation, and validation systems that power our in‑vehicle compute platforms, embedded controllers, and advanced driver‑assistance technologies. You will play a key role in ensuring that Lucid’s software and hardware meet the highest standards of safety, reliability, and performance—supporting everything from firmware development to large‑scale automotive validation.

This role sits at the intersection of DevOps, embedded systems, and automotive test engineering, enabling fast, safe, and scalable development for the world’s most advanced electric vehicles.

What you’ll be doing

• Architect and maintain DevOps pipelines and test automation infrastructure optimized for automotive and embedded development workflows, including cross‑compilation, ECU flashing, and hardware‑in‑the‑loop (HIL) validation
• Build internal tools and services that streamline embedded software testing, firmware deployment, and continuous integration for safety‑critical systems
• Collaborate with Embedded Software, Vehicle Integration, and Test Engineering teams to design scalable test environments for Lucid’s in‑vehicle compute modules and real‑time embedded platforms
• Implement containerized and cloud‑native systems using Docker and Kubernetes to orchestrate distributed test execution across lab and cloud resources
• Integrate automotive‑specific workflows into CI/CD systems, including static analysis, MISRA compliance, traceability, and automated regression testing
• Develop monitoring, logging, and diagnostic tools to ensure high availability and performance of embedded test infrastructure
• Support and extend test frameworks used for ECU validation, vehicle‑level testing, and manufacturing test

What we need to see

• BS/MS in Computer Science, Electrical Engineering, Computer Engineering, or related field
• 5+ years of experience in DevOps, embedded test infrastructure, or automation tooling
• Strong proficiency in Python and experience with frameworks such as Flask or Django
• Experience with embedded Linux, cross‑compilation, and deploying applications to embedded targets
• Familiarity with automotive communication protocols such as CAN bus, or Automotive Ethernet
• Experience with HIL/SIL systems, embedded test benches, or automotive validation environments such as vector Tools
• Proficiency with version control systems such as GIT or GitLab
• Strong Linux knowledge—deployment, debugging, system monitoring, and automation
• Familiarity with bash scripting and Linux‑based automation workflows

Ways to stand out from the crowd

• Background in deploying or maintaining embedded test automation systems, including HIL rigs or ECU validation setups
• Experience with real‑time operating systems (RTOS) or embedded firmware development
• Exposure to manufacturing test environments for automotive ECUs, embedded boards, or in‑vehicle compute modules
• Familiarity with cloud platforms (AWS, Azure, GCP) and infrastructure‑as‑code tools such as Terraform or Ansible
• Passion for building robust CI/CD pipelines and developer‑facing infrastructure for embedded systems

Bonus Qualifications – Agentic AI Tools & Intelligent Automation

Lucid is increasingly leveraging agentic AI systems to accelerate development, automate complex workflows, and enhance test intelligence. Experience with any of the following is a strong plus:

• Building or integrating AI‑driven DevOps agents for automated debugging, test generation, or pipeline optimization
• Experience with LLM‑powered tools for code analysis, anomaly detection, or automated documentation
• Familiarity with AI‑assisted test case generation, including reinforcement‑learning‑based or model‑based testing
• Experience using or developing autonomous agents that interact with CI/CD systems, embedded hardware, or cloud infrastructure
• Knowledge of AI‑driven observability platforms for predictive monitoring, log intelligence, or automated root‑cause analysis
• Understanding of agent orchestration frameworks such as LangChain, LangGraph, or similar tools
• Experience integrating AI agents with automotive workflows such as ECU flashing, HIL orchestration, or embedded diagnostics

Lucid Motors is seeking a Senior SQA and Test Infrastructure Development Engineer to help build the next generation of test, automation, and validation systems that power our in‑vehicle compute platforms, embedded controllers, and advanced driver‑assistance technologies. You will play a key role in ensuring that Lucid’s software and hardware meet the highest standards of safety, reliability, and performance—supporting everything from firmware development to large‑scale automotive validation.

This role sits at the intersection of DevOps, embedded systems, and automotive test engineering, enabling fast, safe, and scalable development for the world’s most advanced electric vehicles.

What you’ll be doing

• Architect and maintain DevOps pipelines and test automation infrastructure optimized for automotive and embedded development workflows, including cross‑compilation, ECU flashing, and hardware‑in‑the‑loop (HIL) validation
• Build internal tools and services that streamline embedded software testing, firmware deployment, and continuous integration for safety‑critical systems
• Collaborate with Embedded Software, Vehicle Integration, and Test Engineering teams to design scalable test environments for Lucid’s in‑vehicle compute modules and real‑time embedded platforms
• Implement containerized and cloud‑native systems using Docker and Kubernetes to orchestrate distributed test execution across lab and cloud resources
• Integrate automotive‑specific workflows into CI/CD systems, including static analysis, MISRA compliance, traceability, and automated regression testing
• Develop monitoring, logging, and diagnostic tools to ensure high availability and performance of embedded test infrastructure
• Support and extend test frameworks used for ECU validation, vehicle‑level testing, and manufacturing test

What we need to see

• BS/MS in Computer Science, Electrical Engineering, Computer Engineering, or related field
• 5+ years of experience in DevOps, embedded test infrastructure, or automation tooling
• Strong proficiency in Python and experience with frameworks such as Flask or Django
• Experience with embedded Linux, cross‑compilation, and deploying applications to embedded targets
• Familiarity with automotive communication protocols such as CAN bus, or Automotive Ethernet
• Experience with HIL/SIL systems, embedded test benches, or automotive validation environments such as vector Tools
• Proficiency with version control systems such as GIT or GitLab
• Strong Linux knowledge—deployment, debugging, system monitoring, and automation
• Familiarity with bash scripting and Linux‑based automation workflows

Ways to stand out from the crowd

• Background in deploying or maintaining embedded test automation systems, including HIL rigs or ECU validation setups
• Experience with real‑time operating systems (RTOS) or embedded firmware development
• Exposure to manufacturing test environments for automotive ECUs, embedded boards, or in‑vehicle compute modules
• Familiarity with cloud platforms (AWS, Azure, GCP) and infrastructure‑as‑code tools such as Terraform or Ansible
• Passion for building robust CI/CD pipelines and developer‑facing infrastructure for embedded systems

Bonus Qualifications – Agentic AI Tools & Intelligent Automation

Lucid is increasingly leveraging agentic AI systems to accelerate development, automate complex workflows, and enhance test intelligence. Experience with any of the following is a strong plus:

• Building or integrating AI‑driven DevOps agents for automated debugging, test generation, or pipeline optimization
• Experience with LLM‑powered tools for code analysis, anomaly detection, or automated documentation
• Familiarity with AI‑assisted test case generation, including reinforcement‑learning‑based or model‑based testing
• Experience using or developing autonomous agents that interact with CI/CD systems, embedded hardware, or cloud infrastructure
• Knowledge of AI‑driven observability platforms for predictive monitoring, log intelligence, or automated root‑cause analysis
• Understanding of agent orchestration frameworks such as LangChain, LangGraph, or similar tools
• Experience integrating AI agents with automotive workflows such as ECU flashing, HIL orchestration, or embedded diagnostics

About You

You are a strong problem‑solver with excellent communication skills, comfortable working in a fast‑paced, cross‑functional environment. You take ownership, collaborate effectively across disciplines, and are motivated by building reliable, secure platforms for cutting‑edge automotive technology.

If you are passionate about embedded systems and autonomous driving and want to make a tangible impact on next‑generation vehicles, we encourage you to apply.

In this role, you are embedded within the ADAS department as a Sr. Technical Program Manager - ADAS/AD Software Development to collaborate with a wide range of cross-functional teams at Lucid Motors on tracking and bringing to completion of all phases of ADAS/AD SW development and release process.    

The Sr. Technical Program Manager - ADAS/AD Software Development will help guide the internal SW development ADAS teams in the development of ADAS and Autonomous Driving SW for Lucid vehicles.  

This role is located on-site at Headquarters in Newark, Ca.  

  Role and Responsibilities   

• Coordinate across platform, applications (Maps, Motion Planning & Control, Perception), and Data teams to create an integrated stack that aligns with feature development  

• Define and track progress toward SW integration milestones and identify, escalate, unblock issues that impact SW Development  

• Manage and coordinate critical program activities between the key stakeholders, cross-functional teams and other project managers/tech leads  

• Manage and coordinate SW release cadences both for ADAS internal validation, and overall system integration and validation milestones     

• Employ project management skills related to overall project tracking, deliverables management, action item tracking, meeting minutes, team communications, and presentations; keep stakeholders apprised of project status and defined deliverables.  

• Use tools like Jira and Confluence to communicate key tasks, track progress, and publish critical information to the complete project team.   

• Contribute to Strategy development and operation management for the entire ADAS/AD department  

Required Qualifications:  

• BS or MS degree in an engineering disciple or equivalent experience  

• 3+ years of experience in technical program management in ADAS SW development, or 7 years of experience in the automotive field, with ADAS/AD features and systems  

• Success in leading cross-functional teams in launching ADAS/AD features into production 

• An ability to lead through ambiguity and enabling teams to perform in this environment  

• Expertise using JIRA, Confluence, and other project management tools  

• Excellent written, presentation, and verbal communication skills and an ability to explain difficult or sensitive information in an easy to understand manner  

• Ability to quickly comprehend complex problems and effectively facilitate the team to a decision and coordinate the action plan.  

• Excellent interpersonal, communication and collaboration skills, with ability to work in a high-pace highly complex cross-functional environment.  

• Strong analytical and quantitative skills with ability to drive decisions using data and metrics   

Preferred Qualifications:  

• Previous project management experience from an OEM or a Tier1 in ADAS/AD SW development, or feature definition and systems engineering  

• Previous experience with lean-agile framework, and development and deployment process   

• Knowledge of relevant regulations and applicable safety standards for typical ADAS features (e.g. ASPICE, FMVSS, EuroNCAP, R79, GSR2, etc.)  

• MS or PhD in Computer Science, Electrical Engineering, System Engineering, or similar preferred 

Responsibilities:

· Design, prototype, test, and deploy state-of-the-art behavior planning algorithms for autonomous and assisted driving features.

· Develop and implement decision-making, trajectory and route planning, and optimization-based planning frameworks.

· Collaborate closely with perception, controls, localization, and systems teams to ensure robust and efficient integration of planning software.

· Drive innovation through the invention of novel algorithms and features that elevate the safety, comfort, and intelligence of Lucid vehicles.

· Support the validation and verification of behavior planning components in simulation, hardware-in-the-loop (HIL), and on-road testing environments.

Required Qualifications:

· MS degree in Robotics, Computer Science, Aerospace Engineering, Mechanical Engineering, or a related field (or equivalent experience).

· 2+ years of professional experience, or a Ph.D. in a relevant discipline.

· Strong C++ programming skills with a solid understanding of software engineering best practices.

· Deep knowledge of decision-making algorithms such as graph/tree search methods or AI-based planners.

· Experience with motion and behavior planning concepts including decision-making under uncertainty, optimization techniques, trajectory generation, and route planning.

· Hands-on experience with embedded systems integration in robotics or automotive domains.

· Strong communication and problem-solving skills.

Preferred Qualifications:

· Experience with middleware systems such as ROS or DDS.

· Proficiency in scripting languages such as Python, Bash.

· Experience with simulation tools (e.g., Gazebo, CARLA) and frameworks for testing autonomous systems.

· Experience and understanding of deep learning frameworks (e.g., TensorFlow, PyTorch).

· Experience and knowledge of imitation/reinforcement learning techniques.

· Familiarity with version control systems (e.g., Git) and modern development workflows.

· Prior work on scenario-based testing, MIL/SIL/HIL environments, or automated test frameworks.

· Exposure to CI tools such as Jenkins or GitLab CI.

Key Responsibilities

• Design, develop, and optimize embedded platform software for automotive ADAS and autonomous driving systems
• Perform board bring‑up and develop low‑level device drivers for SoC peripherals
• Lead camera bring‑up activities, including ISP integration and validation
• Develop and integrate video pipelines, including video codecs and secure RTP streaming
• Collaborate closely with hardware, systems, and application teams to ensure seamless hardware–software integration
• Support platform stability, performance optimization, and production readiness

Required Qualifications

• 5+ years of experience in embedded software development for complex systems
• Strong proficiency in C/C++
• Hands‑on experience with Linux and/or QNX kernel, BSP, and low‑level platform development
• Solid experience with board bring‑up and device driver development, including interfaces such as I2C, UART, SPI, PCIe, RGMII, SGMII, and camera ISPs
• Experience working with real‑time operating systems (RTOS)

Preferred Qualifications

• Advanced C++ application development experience
• Prior experience in ADAS or autonomous driving systems
• Ability to read and interpret hardware schematics, datasheets, and reference designs
• Experience with bootloaders, secure boot, firmware update mechanisms, and UDS diagnostics
• Strong understanding of embedded security concepts, including cryptographic hardware, key management, and certificate management

About You

You are a strong problem‑solver with excellent communication skills, comfortable working in a fast‑paced, cross‑functional environment. You take ownership, collaborate effectively across disciplines, and are motivated by building reliable, secure platforms for cutting‑edge automotive technology.

If you are passionate about embedded systems and autonomous driving and want to make a tangible impact on next‑generation vehicles, we encourage you to apply.

Lucid Motors is seeking a Staff QA and Test Infrastructure Development Engineer to help build the next generation of test, automation, and validation systems that power our in‑vehicle compute platforms, embedded controllers, and advanced driver‑assistance technologies. You will play a key role in ensuring that Lucid’s software and hardware meet the highest standards of safety, reliability, and performance—supporting everything from firmware development to large‑scale automotive validation.

This role sits at the intersection of DevOps, embedded systems, and automotive test engineering, enabling fast, safe, and scalable development for the world’s most advanced electric vehicles.

What you’ll be doing

• Architect and maintain DevOps pipelines and test automation infrastructure optimized for automotive and embedded development workflows, including cross‑compilation, ECU flashing, and hardware‑in‑the‑loop (HIL) validation
• Build internal tools and services that streamline embedded software testing, firmware deployment, and continuous integration for safety‑critical systems
• Collaborate with Embedded Software, Vehicle Integration, and Test Engineering teams to design scalable test environments for Lucid’s in‑vehicle compute modules and real‑time embedded platforms
• Implement containerized and cloud‑native systems using Docker and Kubernetes to orchestrate distributed test execution across lab and cloud resources
• Integrate automotive‑specific workflows into CI/CD systems, including static analysis, MISRA compliance, traceability, and automated regression testing
• Develop monitoring, logging, and diagnostic tools to ensure high availability and performance of embedded test infrastructure
• Support and extend test frameworks used for ECU validation, vehicle‑level testing, and manufacturing test

What we need to see

• BS/MS in Computer Science, Electrical Engineering, Computer Engineering, or related field
• 8+ years of experience in DevOps, embedded test infrastructure, or automation tooling
• Strong proficiency in Python and experience with frameworks such as Flask or Django
• Experience with embedded Linux, cross‑compilation, and deploying applications to embedded targets
• Familiarity with automotive communication protocols such as CAN bus, or Automotive Ethernet
• Experience with HIL/SIL systems, embedded test benches, or automotive validation environments such as vector Tools
• Proficiency with version control systems such as GIT or GitLab
• Strong Linux knowledge—deployment, debugging, system monitoring, and automation
• Familiarity with bash scripting and Linux‑based automation workflows

Ways to stand out from the crowd

• Background in deploying or maintaining embedded test automation systems, including HIL rigs or ECU validation setups
• Experience with real‑time operating systems (RTOS) or embedded firmware development
• Exposure to manufacturing test environments for automotive ECUs, embedded boards, or in‑vehicle compute modules
• Familiarity with cloud platforms (AWS, Azure, GCP) and infrastructure‑as‑code tools such as Terraform or Ansible
• Passion for building robust CI/CD pipelines and developer‑facing infrastructure for embedded systems

Bonus Qualifications – Agentic AI Tools & Intelligent Automation

Lucid is increasingly leveraging agentic AI systems to accelerate development, automate complex workflows, and enhance test intelligence. Experience with any of the following is a strong plus:

• Building or integrating AI‑driven DevOps agents for automated debugging, test generation, or pipeline optimization
• Experience with LLM‑powered tools for code analysis, anomaly detection, or automated documentation
• Familiarity with AI‑assisted test case generation, including reinforcement‑learning‑based or model‑based testing
• Experience using or developing autonomous agents that interact with CI/CD systems, embedded hardware, or cloud infrastructure
• Knowledge of AI‑driven observability platforms for predictive monitoring, log intelligence, or automated root‑cause analysis
• Understanding of agent orchestration frameworks such as LangChain, LangGraph, or similar tools
• Experience integrating AI agents with automotive workflows such as ECU flashing, HIL orchestration, or embedded diagnostics

We are seeking a Sr. Motion Planning and Controls Engineer, Autonomous Driving to design, develop, and deploy industry-leading planning and control algorithms for next-generation driver assistance and autonomous systems.  

This position is based in Newark, CA and requires onsite presence five days a week.  

The Role:  

As a Sr. Motion Planning and Controls Engineer, you will play a key role in developing high-performance motion planning and control features for Lucid’s ADAS and autonomous driving systems. You’ll work across software, hardware, and systems teams to ensure robust design, testing, and deployment of production-grade lateral and longitudinal control algorithms.  

Responsibilities:  

• Design, prototype, test, and deploy motion planning and control algorithms for ADAS and autonomous driving systems.  

• Implement state-of-the-art approaches to trajectory planning, route planning, and real-time control.  

• Develop and tune classical and modern controllers (e.g., LQR, MPC, PID, Adaptive, Robust) for both lateral and longitudinal vehicle dynamics.  

• Conduct model-based design and validation using MATLAB/Simulink or equivalent tools.  

• Participate in the full development cycle, from simulation and SIL/HIL testing to in-vehicle implementation and release.  

• Collaborate closely with systems, validation, perception, and platform teams to ensure safe and seamless software integration.  

• Contribute to architectural decisions, safety assessments, and product scalability.  

Required Qualifications:  

• Bachelor’s degree in Automotive, Aerospace, Mechanical Engineering or a related field (advanced degrees preferred).  

• 5+ years of experience (with MS) or 3+ years (with PhD) in motion control or trajectory planning for ADAS/Autonomous Driving.  

• Deep knowledge of control system design and real-time implementation using modern control approaches (e.g., LQR, MPC).  

• Proven experience deploying lateral and longitudinal controllers in a production or research vehicle environment.  

• Proficiency in modeling and simulation tools (e.g., MATLAB/Simulink).  

• Solid understanding of ADAS/AD systems, robotics, and vehicle dynamics.  

• Strong communication skills and ability to thrive in a fast-paced, collaborative environment.  

Preferred Qualifications:  

• Proficiency in programming languages such as C++, Python, and MATLAB.  

• Experience with middleware frameworks like ROS.  

• Familiarity with AUTOSAR and embedded software development practices.  

• Experience in bench testing, SIL/HIL integration, and scenario-based simulation.  

• Knowledge of safety standards and automotive system regulations (e.g., ISO 26262).  

• Background in agile development environments, version control (e.g., Git), and static code analysis. 

We are currently seeking Staff System Engineer – ADAS/AD Safety to join our ADAS/AD team.

We are looking for a system safety engineer who will lead the functional safety (ISO 26262) and SOTIF foundation for our ADAS features, while also owning the safety case framework for our higher-level automated driving functions. This role establishes the core safety processes, artifacts, and safety case architecture that the company will scale as our products evolve.

This is a hands-on technical role with significant influence on process, tooling, and culture. You will be the internal reference for safety case thinking and modern safety standards (ISO 26262, SOTIF, UL 4600, etc.).

This role is located on-site at Headquarters in Newark, CA.

Role Responsibilities:

· Collaborate with the Function Safety team to jointly review and align on HARA, Safety Goals (SG), for ADAS and AD features.

· Own the derivation and authoring of Technical Safety Concepts and Technical Safety Requirements, ensuring proper allocation to sensors, ECUs, software modules, actuators, vehicle networks, and operational assets.

· Integrate SOTIF thinking into the safety case: performance limitations, triggering conditions, misuse and edge-case scenarios, especially for perception and AI/ML components.

· Define and own the end-to-end safety case framework for ADAS/AD stack (structure, claims, argumentation style, and evidence model).

· Identify top-level safety objectives and transform them into safety case claims, sub-claims, and required evidence (e.g., using GSN or equivalent notations).

· Act as the technical focal point for safety case topics in design reviews, release gates, and change control boards.

· Contribute to building a Safety Management System (SMS) and safety governance structures over time (e.g., safety board, safety metrics).

Required Qualifications:

· Bachelors in System Engineering, Electrical Engineering, Computer Science

· 8+ years of related experience in system safety, functional safety, or safety assurance for autonomous systems, ADAS, robotics, or similar safety-critical domains.

· Demonstrated experience with at least one full safety lifecycle (concept through SOP/launch) for a complex system.

· Hands-on experience with safety case development or maintenance, including structuring claims, arguments, and evidence

· Solid working knowledge of ISO 26262, ISO 21448 (SOTIF) and UL 4600

· Practical experience with safety analysis methods (e.g., HARA, FMEA, FTA, STPA) and their integration into a traceable safety argument.

· Strong written communication skills; able to author clear safety concepts, analyses, and safety case documentation targeted at both engineers and leadership.

· Strong systems thinking: comfortable reasoning from high-level societal/operational risk down to implementation details.

· High ownership bias: willing to create structure where none exists and drive alignment across teams.

· Ability to influence without authority and bring engineers, PMs, and leaders along on safety decisions.

· Clear, concise communication; able to explain complex safety trade-offs to both technical and non-technical audiences.

Preferred Qualifications:

· Master’s degree in system engineering, Electrical Engineering, Computer Science experience

· 6 years related experience or a PhD with 3 years experience

· Experience with automated driving or advanced ADAS (multi-sensor stacks: camera, radar, lidar, ultrasonic, GNSS/IMU, HD maps).

· Demonstrated ownership of a UL 4600-aligned safety case or similar safety case for autonomy.

· Working knowledge of ISO-8800

· Familiarity with AI/ML safety topics (data pipeline safety, performance monitoring, ODD/OSD concepts, SOTIF for perception/behavior).

· Experience working in or with fast-moving startups or new product lines, balancing rigor with pragmatism.

· Exposure to regulatory interactions, external audits, or certification bodies on safety topics.

About Lucid 

At Lucid, we are redefining the luxury electric vehicle experience, combining cutting-edge technology with exceptional design to deliver intuitive, safe, and exhilarating mobility. Join our team and help shape the future of autonomous driving. 

The Role 

We are seeking a Staff Software Engineer to lead the integration and deployment of advanced perception models into Lucid’s production ADAS and autonomous driving systems. This role focuses on productizing ML models, ensuring robust performance on automotive-grade hardware, and building scalable pipelines for deployment and validation. You will collaborate with ML researchers, perception engineers, and hardware teams to deliver high-performance, safety-compliant solutions. 

Key Responsibilities 

• Model Integration & Productization  

• Deploy and integrate perception models (camera, LiDAR) into Lucid’s centralized software stack. 

• Transition experimental components into production-ready modules with robust scheduling and diagnostics. 

• Performance Optimization  

• Optimize inference pipelines using CUDA, TensorRT, and mixed-precision techniques for real-time performance. 

• Implement multithreaded scheduling and containerized deployments for automotive platforms. 

• Pipeline Development & Automation  

• Build CI/CD pipelines for nightly deployments, HIL verification, and KPI reporting. 

• Automate data recording, evaluation frameworks, and regression testing. 

• Cross-Functional Collaboration  

• Work closely with ML researchers, software engineers, and OEM partners to ensure seamless integration. 

• Support SDK development and customer-facing deliverables. 

• System Diagnostics & Monitoring  

• Implement runtime performance metrics, logging, and error reporting for perception stack reliability. 

Required Qualifications 

• BS/MS in Computer Science, Electrical Engineering, or related field. 

• 7+ years of experience in software engineering for perception or autonomous systems. 

• Strong proficiency in C++ and Python, with experience in ROS1/2, OpenCV, and GPU acceleration. 

• Hands-on experience with ML frameworks (PyTorch) and inference optimization (TensorRT, CUDA). 

• Expertise in containerization (Docker), CI/CD, and automated deployment pipelines. 

• Proven ability to lead technical projects and collaborate across teams. 

Preferred Qualifications 

• Experience with automotive perception systems and ADAS software stacks. 

• Familiarity with automotive safety standards (ISO 26262, ASPICE). 

• Knowledge of multithreaded scheduling and real-time performance tuning. 

• Background in SDK development and automotive customer integration. 

We are seeking a Senior Simulation & Software Integration Engineer to take full ownership of our next-generation autonomous driving simulation platform. This is not a "pure software" role; we need a hybrid engineer who understands the physics and complexities of automotive systems as deeply as the code that simulates them.

You will be the bridge between abstract autonomy algorithms and real-world vehicle behavior. You won’t just follow a spec—you will define the requirements, think creatively to solve bottleneck issues in SIL/HIL, and implement the "next-gen" workflows that allow Lucid to validate ADAS features at a global scale. If you are a problem-solver who enjoys getting your hands dirty in both C++ and vehicle dynamics, this is your role.

Key Responsibilities

• End-to-End Ownership: Drive the design and implementation of simulation pipelines. You will take high-level ADAS requirements and turn them into functional, scalable simulation scenarios.
• Hybrid Integration: Build and maintain the "glue" between our autonomy software stack and simulation engines. You will ensure that the software behaves identically whether it’s in a cloud-native SIL environment or a bench-top HIL rack.
• Creative Problem Solving: Identify gaps in current simulation capabilities (e.g., sensor fidelity, edge-case generation) and implement "out-of-the-box" solutions using modern tools like CARLA, Unreal Engine, or generative AI.
• Validation Frameworks: Define and implement the KPIs and automated metrics that determine if a new software build is "safe" for the road.
• Technical Mentorship: Act as a senior lead within the simulation team, triaging complex integration bugs that span across software, hardware, and infrastructure layers.

Qualifications (The "Must-Haves")

• The Hybrid Mindset: Strong software engineering fundamentals (Modern C++, Python) combined with a solid grasp of how a vehicle actually moves and thinks.
• Ownership Pedigree: Proven track record of taking a simulation project from "concept" to "production validation."
• Simulation Power User: Professional experience with automotive simulators (CARLA, IPG CarMaker, or VTD) and scenario standards (OpenSCENARIO, OpenDRIVE).
• Infrastructure Fluency: Comfortable with Docker and CI/CD pipelines. You should know how to containerize a simulator to run 10,000 tests in the cloud.
• Systems Debugger: Exceptional ability to triage issues where the root cause could be anything from a race condition in the code to a misconfigured vehicle plant model.

Great to Have (The "Differentiators")

• HIL Expertise: Experience with dSPACE, NI, or Vector hardware, including ARXMLs and rest-bus simulation.
• Physics & Sensors: Deep understanding of vehicle dynamics (multi-body) or the physics of Lidar/Radar/Camera sensor modeling.
• Next-Gen Tech: Experience applying Generative AI or Neural Simulation to create realistic driving environments.
• Middleware Mastery: Deep knowledge of ROS2, DDS, or custom high-performance IPCs.

Education & Experience

• Bachelor’s or Master’s degree in Mechanical Engineering, Robotics, Computer Science, or a related field. We value the "Automotive + SW" crossover highly.
• 5+ years of professional experience in ADAS/AD simulation or software integration.

 The Role  

We are seeking a Senior Machine Learning Engineer (or strong ML Engineer) to drive the integration and deployment of advanced perception models into Lucid’s production ADAS and autonomous driving systems. This role focuses on model optimization and compression, productizing ML models, ensuring robust performance on automotive-grade hardware, and building scalable pipelines for deployment and validation. You will collaborate with ML researchers, perception engineers, and hardware teams to deliver high-performance, safety-compliant solutions. 

Key Responsibilities 

• Model Integration & Productization 

• Deploy and integrate perception models into Lucid's centralized software stack. 

• Transition experimental components into production-ready modules with robust scheduling and diagnostics. 

• Model Optimization & Compression 

• Optimize inference pipelines using CUDA, TensorRT, mixed-precision, quantization (PTQ/QAT), and model pruning/distillation techniques for real-time performance. 

• Profile latency, memory, and compute bottlenecks; improve model and system efficiency on automotive hardware. 

• Pipeline Development & Automation 

• Build CI/CD pipelines for nightly deployments, HIL verification, and KPI reporting. 

• Automate data recording, evaluation frameworks, and regression testing for optimized models. 

• Cross-Functional Collaboration 

• Work closely with ML researchers, software engineers, and hardware/platform teams to ensure seamless integration. 

• Support SDK/tooling development and internal or customer-facing deliverables. 

• System Diagnostics & Monitoring 

• Implement runtime performance metrics, logging, and error reporting for perception stack reliability. 

Required Qualifications 

• BS/MS in Computer Science, Electrical Engineering, or related field. 

• For Senior ML Engineer: 5+ years (or ML Engineer: 2+ years) of experience in ML/software engineering for perception or autonomous systems. 

• Strong proficiency in C++ and Python, with experience in ROS1/2, OpenCV, and GPU acceleration. 

• Hands-on experience with ML frameworks (PyTorch) and inference optimization (TensorRT, CUDA). 

• Practical experience with at least one compression technique such as quantization, pruning, or distillation. 

• Experience with containerization (Docker), CI/CD, and automated deployment pipelines. 

• Strong collaboration skills and ability to execute across research and production teams. 

Preferred Qualifications 

• Experience with automotive perception systems and ADAS software stacks. 

• Familiarity with automotive safety standards (ISO 26262, ASPICE). 

• Experience deploying INT8/FP16 models and validating accuracy-latency tradeoffs. 

• Knowledge of multithreaded scheduling and real-time performance tuning. 

• Background in SDK/tooling development and automotive customer integration.