Summary
We are seeking an experienced Machine Learning and Autonomous Driving Algorithms Engineer to develop, integrate, validate, and deploy production software for parking assistance and low-speed autonomous-driving systems. The role requires strong expertise in machine learning, Python software development, scalable data and training pipelines, and algorithm validation in real-world environments.
The engineer will work closely with algorithm, software, systems, validation, and vehicle integration teams to solve challenging perception, localization, sensor-fusion, state-estimation, threat-assessment, and planning problems. This position will support global L0-L3 autonomous-driving programs and drive technical initiatives from concept through production deployment while following a rigorous V-cycle and safety-focused development process.
Responsibilities and Duties
- Develop 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 algorithms using Python and frameworks such as PyTorch and/or TensorFlow.
- Design, implement, and maintain scalable ML training, evaluation, and data-processing pipelines.
- Work with large-scale datasets to improve model performance, robustness, and generalization.
- Develop and optimize modern deep-learning models, including Transformer-based neural networks.
- Validate algorithms through simulation, laboratory testing, proving-ground evaluation, real-vehicle testing, and real-road testing.
- Improve algorithm performance across diverse environments, operating conditions, vehicle platforms, and global customer programs.
- Perform root-cause analysis of model failures, missed detections, false detections, performance regressions, and safety-related issues.
- Use data-centric methods, including data-quality improvement, dataset balancing, scenario coverage, labeling strategy, and targeted data collection, to improve model performance.
- 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 and reliable autonomous-driving operations.
- Investigate challenging perception and sensor-fusion problems involving cameras, ultrasonic sensors, radar, lidar, and other vehicle sensors.
- Design and execute functional-performance tests and confirm compliance with system and customer requirements.
- Apply a disciplined V-cycle development process to support safety-critical automotive software and electronics.
- Collaborate with downstream software, systems, validation, and integration teams to support globally deployed L0-L3 autonomous-driving systems.
- Work in Linux development environments using Git-based workflows, code reviews, automated testing, and CI/CD practices.
- Support cloud-native or AWS-based ML infrastructure and scalable platforms used by multiple engineering teams.
- Drive technical initiatives from initial concept and experimentation through algorithm maturation, vehicle integration, validation, and production deployment.
- Communicate technical findings clearly and work analytically, creatively, and collaboratively to resolve complex engineering problems
Must Have (Basic Qualifications)
Education
- Master's degree in Computer Science, Electrical Engineering, Robotics, Artificial Intelligence, Machine Learning, Applied Mathematics, or equivalent.
- 8+ years of industry experience developing production software and algorithms.
- PhD may substitute for a portion of experience.
Machine Learning
- 5+ years hands-on experience developing and deploying machine learning algorithms.
- Strong understanding of:
- supervised learning
- deep learning
- model evaluation
- dataset development
- error analysis
- Experience with PyTorch and/or TensorFlow.
Software Development
- Strong Python development experience.
- Experience building scalable software systems.
- Experience working in Linux development environments.
- Proficiency with Git-based development workflows and CI/CD practices.
Data & Training Pipelines
- Experience designing, implementing, or maintaining ML training pipelines.
- Experience with large-scale datasets and data processing workflows.
- Experience performing root-cause analysis of model failures and performance regressions.
Cross-Functional Execution
- Experience working with algorithm, software, systems, and validation teams.
- Demonstrated ability to drive technical initiatives from concept through production deployment.
Prefer to Have (Preferred Qualifications)
Modern Deep Learning
- Experience developing Transformer-based neural networks.
- Experience with:
- Vision Transformers
- Multi-modal architectures
- Foundation Models
- Generative AI techniques
- Experience optimizing and scaling large-model training.
Autonomous Driving / Robotics
- Experience developing perception, prediction, localization, planning, or sensor-fusion algorithms.
- Experience working with:
- camera
- radar
- lidar
- ultrasonic
- vehicle signals
- Experience shipping production ADAS or autonomous-driving features.
MLOps & Cloud Infrastructure
- Experience with AWS or cloud-native ML infrastructure.
- Experience with:
- experiment tracking
- model registry
- automated retraining
- model deployment pipelines
- continuous evaluation
- Experience building scalable ML platforms used by multiple teams.
Data-Centric AI
- Experience with:
- annotation workflows
- active learning
- synthetic data generation
- data quality metrics
- scenario mining
- Experience improving model performance through data strategy rather than architecture changes alone.
Sensor Fusion and Localization
- Experience with:
- sensor fusion
- probabilistic estimation
- Kalman filtering
- SLAM
- factor graph optimization
Traits We Seek
- Curiously investigate everything – ability to solving problems analytically, creatively and collaboratively
- Seriously execute V-cycle procedure – a mindset to develop safety electronics to enhance driving safety
- Learn by doing – an entrepreneurial mindset that’s driven by hands-on experimentation
- Embrace resilience – seeing every challenge as a learning opportunity and invitation to grow
Aptiv Rewards and Advantages
- Competitive compensation with bonus potential
- Competitive health benefits
- 401K with matching contribution
- Learning and development opportunities
- Discount programs with various manufacturers and retailers
- Recognition for innovation and excellence
- Opportunities to give back to the community
- Meaningful work that makes a difference in the world
- Relocation assistance (if applicable)
YOUR BENEFITS AT APTIV:
- Private health care effective day 1 of employment
- Life and accident insurance
- Paid Time Off (Holidays, Vacation, Designated time off, 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
APPLY TODAY, AND TOGETHER LET’S CHANGE TOMORROW!
