Senior Engineer - Algorithms

Description

The company builds parking assistance and low-speed autonomous-driving systems, and this role supports its global L0-L3 programs.

You will work with algorithm, software, systems, validation and vehicle integration teams on perception, localization, sensor fusion, state estimation, threat assessment and planning. You will take technical work from early concept through production, following a strict V-cycle and a safety-first process.

The role needs strong machine learning and Python skills, experience with scalable data and training pipelines, and algorithm validation on real vehicles and roads.

Responsibilities

• Build perception, localization, prediction, planning, sensor-fusion, state-estimation and threat-assessment algorithms for autonomous-driving and parking functions.
• Design, integrate, test and release production software and algorithms for internal and external customers.
• Develop and deploy machine learning models in Python using PyTorch and/or TensorFlow.
• Design, build and maintain scalable pipelines for ML training, evaluation and data processing.
• Work with large datasets to make models more accurate, robust and general.
• Develop and tune modern deep learning models, including Transformer-based networks.
• Test algorithms in simulation, the lab, proving grounds, and on real vehicles and real roads.
• Improve algorithm performance across varied environments, operating conditions, vehicle platforms and global customer programs.
• Find root causes of model failures, missed and false detections, performance regressions and safety issues.
• Improve models through data work: data quality, dataset balance, scenario coverage, labeling strategy and targeted data collection.
• Develop algorithms for parking-space recognition, parking-line detection, object recognition, obstacle detection, localization, vehicle alignment and parking control.
• Support state estimation and threat assessment for safe, reliable autonomous driving.
• Investigate perception and sensor-fusion problems involving cameras, ultrasonic sensors, radar, lidar and other vehicle sensors.
• Design and run functional performance tests and confirm the system meets system and customer requirements.
• Follow a disciplined V-cycle process for safety-critical automotive software and electronics.
• Work with downstream software, systems, validation and integration teams on globally deployed L0-L3 systems.
• Work in Linux using Git workflows, code reviews, automated testing and CI/CD.
• Support cloud-native or AWS-based ML infrastructure used by several engineering teams.
• Lead technical initiatives from early experimentation through algorithm maturity, vehicle integration, validation and production.
• Explain technical findings clearly and solve complex engineering problems analytically, creatively and collaboratively.

Requirements

• A Master's degree in Computer Science, Electrical Engineering, Robotics, Artificial Intelligence, Machine Learning, Applied Mathematics or an equivalent field.
• 8+ years of industry experience shipping production software and algorithms. A PhD can replace part of this experience.
• 5+ years of hands-on experience building and deploying machine learning algorithms.
• Solid understanding of supervised learning, deep learning, model evaluation, dataset development and error analysis.
• Experience with PyTorch and/or TensorFlow.
• Strong Python skills and experience building scalable software systems.
• Experience in Linux, with Git-based workflows and CI/CD practices.
• Experience designing, building or maintaining ML training pipelines and handling large datasets and data processing workflows.
• Experience finding root causes of model failures and performance regressions.
• Experience working with algorithm, software, systems and validation teams, and taking technical initiatives from concept to production.
• Experience developing Transformer-based networks, plus some of: Vision Transformers, multi-modal architectures, foundation models or generative AI techniques.
• Experience optimizing and scaling large-model training.
• Experience developing perception, prediction, localization, planning or sensor-fusion algorithms.
• Experience with camera, radar, lidar, ultrasonic and vehicle signal data.
• Experience shipping production ADAS or autonomous-driving features.
• Experience with AWS or cloud-native ML infrastructure.
• Experience with experiment tracking, model registry, automated retraining, model deployment pipelines and continuous evaluation.
• Experience building ML platforms used by multiple teams.
• Experience with annotation workflows, active learning, synthetic data generation, data quality metrics and scenario mining.
• Experience improving model performance through data strategy, not just architecture changes.
• Experience with sensor fusion, probabilistic estimation, Kalman filtering, SLAM and factor graph optimization.

Conditions

Global, cross-team role supporting L0-L3 autonomous-driving programs.

The company values inclusion and welcomes people from all backgrounds.

Benefits

• Private health care from day 1 of employment.
• Life and accident insurance.
• Paid time off covering holidays, vacation, designated time off and parental leave.
• Relocation assistance may be available.
• Learning and development opportunities.
• Discount programs with various manufacturers and retailers.
• Recognition for innovation and excellence.
• Opportunities to give back to the community.
• Tuition reimbursement.