Sr. Control Algorithm Engineer (Multi-Camera Vision Control)
직무 설명
This position is with STRADVISION Seoul Office
[About STRADVISION]
We Empower Everything To Perceive Intelligently
STRADVISION is a global deep-tech company specializing in autonomous driving and vision AI, making life safer and better through AI-based camera perception technology. Since its founding in 2014, the company has developed and commercialized core AI technologies that accurately perceive and interpret the world around us. In 2026, STRADVISION became the first autonomous driving software company to be listed on KOSDAQ. Today, approximately 250 colleagues work together across eight offices worldwide.
STRADVISION has secured contracts to supply its camera perception software, SVNet, to 14 global automakers for more than 50 vehicle models. SVNet has been deployed in over five million production vehicles. STRADVISION won the Gold Award for “Best-in-Class Software for Perception Systems” at the AutoSens Awards for two consecutive years, in 2021 and 2022.
The company is now expanding the reach of vision AI beyond autonomous driving into robotics and physical AI. Join us in shaping the future of mobility and physical AI.
[Our Story]
🔎 STRADVISION’s Core Technology
🔎 STRADVISION's Perks & Benefits
Latest News from STRADVISION
📌 STRADVISION Unveils Its SVDataFlow Pipeline, Focusing on Technical Advancement and Scalability
[Our Technology]
- In 2019, STRADVISION became the world’s first deep learning-based startup to achieve ASPICE CL2 certification. In 2020, the company received the AVT ACES Autonomous Vehicle Innovation Award.
- STRADVISION won the Gold Award for “Best-in-Class Software for Perception Systems” at the AutoSens Awards for two consecutive years, in 2021 and 2022.
- In August 2022, STRADVISION closed a KRW 107.6 billion Series C funding round, with Aptiv of the United States and ZF Group of Germany participating as strategic investors, reflecting global recognition of the company’s technology.
- STRADVISION holds 168 U.S. patents related to AI and automotive technology and continues to invest actively in research and development to further strengthen its technological capabilities.
- In the first half of 2026, the cumulative number of vehicles equipped with SVNet exceeded five million worldwide. STRADVISION continues to grow despite an economic slowdown and intensifying industry competition.
- In 2025, STRADVISION ranked 10th in Korea’s AI competitiveness rankings, behind companies such as Samsung Electronics, NAVER, and LG.
[Mission of the Role]
The Role as "Guardian of Physical Reality"
In an organization introducing E2E models, the Senior Control Engineer's role evolves beyond a simple path tracker to become the ultimate "Guardian of Physical Reality." They are the last line of defense against the unpredictable outputs of a learning-based system. While an E2E model may learn to map sensor inputs directly to control commands like steering angle 2, this learned mapping does not inherently guarantee stability, smoothness, or adherence to the vehicle's physical limits (e.g., max steering rate, tire friction limits).
The Senior Control
Engineer's most critical, forward-looking task is therefore to build a safety cage around the E2E model. This is a sophisticated "guardian" system that might take the E2E model's intended behavior as a soft constraint or goal, but which enforces hard constraints based on a trusted vehicle dynamics model. It ensures that even if the AI has a "crazy idea," the vehicle either executes it safely or reverts to a safe state. This role requires a deep, principled understanding of control theory and physics to provide checks and balances for a powerful but potentially volatile large neural network.
The Opportunity: Mastering the Physics of Motion
This role is the critical link between the digital plan and the physical world. You will be responsible for translating the planner's intent into flawless, stable, and comfortable vehicle motion. You will own the vehicle's dynamic soul, ensuring that every maneuver—whether calculated by a classical planner or generated by a neural network—is executed with the utmost precision and safety.
This role is a unique opportunity to work on high-impact, cutting-edge research that directly contributes to the development of next-generation autonomous driving systems.
[Key Responsibilities]
Modular Stack (The Foundation)
- Design, implement, and tune high-performance longitudinal and lateral vehicle controllers, with an emphasis on Model Predictive Control (MPC) for its strength in handling complex constraints and previewing the planned path.
- Develop high-fidelity vehicle dynamics models for use in simulation and control logic design, and continuously improve model accuracy and perform system identification using deep learning based on real-world driving data.
- Apply data-driven deep learning techniques to develop adaptive control logic that dynamically tunes control parameters in response to real-time changing driving conditions (e.g., road surface, tire wear), thereby increasing robustness.
- Design and implement state estimators (e.g., Extended/Unscented Kalman Filters) to estimate key vehicle states that cannot be directly measured (e.g., velocity, slip angle, road grade).
- Work hands-on with vehicle hardware, interfacing with ECUs, sensors, and actuators via CAN/Ethernet, and lead in-vehicle tuning and validation efforts.
End-to-End Stack (The Frontier)
- Ensure the stability and physical realism of control outputs generated directly by E2E models. This may involve designing post-processing filters, in-network stability-enhancing layers, or rate limiters.
- Research and develop a "Guardian" controller: a safety-first underlying control system that monitors the E2E policy's commands and intervenes to prevent violations of safety or comfort boundaries.
- Collaborate with the E2E team to incorporate vehicle dynamics constraints directly into the learning process, either by using differentiable physics models or by shaping the policy's action space.
- Define metrics for "control quality" (e.g., ride comfort, smoothness, tracking accuracy) and use them to evaluate and provide feedback on the performance of different E2E policy versions.
Collaboration
- Collaborate with cross-functional teams, including machine learning engineers, software integration engineers, hardware platform engineers, and quality assurance, to integrate multi-vision E2E algorithms into ADAS systems.
- Participate in code reviews and knowledge-sharing sessions to foster a collaborative work environment.
Mentoring and Technical Guidance
- Mentor and provide technical guidance to junior/entry engineers.
[Basic Qualifications]
- Master's or Ph.D. in Mechanical, Electrical, Aerospace Engineering, Robotics, or a related field.
- 7+ years of experience designing dynamic system controllers in the automotive, robotics, or aerospace industries.
- Deep expertise in modern control theory (state-space, LQR, MPC) and classical control (PID).
- High proficiency in MATLAB/Simulink for model-based design and expert-level C++ ability for embedded implementation.
- Solid understanding of vehicle dynamics and modeling.
[Preferred Qualifications]
- Experience deploying controllers on real vehicles, including SIL/HIL testing and real-world vehicle calibration.
- Understanding of automotive safety standards like ISO 26262 and communication protocols like CAN, FlexRay, and Automotive Ethernet.
- Experience with system identification techniques for extracting model parameters from test data.
- Applied experience in numerical optimization and control.
[Application]
- Required: Resume / Thesis (for those who have a Master’s degree or above.)
- Optional: Cover Letter, Research/Project Portfolio (including publications, open-source projects, or patents), Other theses
- Application Review > Screening Test > Interview(s) > Reference Check > Offer > Onboarding
- Please be aware of that the recruitment processes & schedules may be changed depending on the job and/or other circumstances.
[Others]
- This position is open for ongoing recruitment and may close earlier once the role has been successfully filled.
- A 3-month probationary period will apply after joining as a regular employee.
- Visa sponsorship can be supported for eligible international candidates.
- If any false or inaccurate information is identified during the hiring process, the recruitment may be discontinued or an offer may be withdrawn.
STRADVISION stands for an open and respectful corporate culture because we believe the diversity helps us to find new perspectives.
STRADVISION ensures that all our members have equal opportunities –regardless of age, ethnic origin and nationality, gender and gender identity, physical and mental abilities, religion and belief, sexual orientation, and social background. We always ensure diversity right from the recruitment stage and therefore make hiring decisions based on candidate’s actual competencies, qualifications, and business needs at the point of the time.
Please feel free to contact us via our HR team e-mail if you have any questions.
[STRADVISION HR Team e-mail: [email protected]]
이 직무에 관심이 있으신가요?