Senior Engineer - Algorithms

Posted One Month Ago
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Troy, MI, USA
In-Office
Senior level
Automotive
The Role
Develop and deploy machine-learning and autonomous-driving algorithms for parking assistance and low-speed autonomy. Responsibilities include perception, localization, sensor fusion, planning, state estimation, threat assessment, deep-learning model development, scalable training pipelines, data-centric optimization, and real-world validation. The role collaborates across software, systems, validation, and vehicle integration teams while supporting safety-critical production deployments through a rigorous V-cycle process.
Summary Generated by Built In

Role 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

Your Background

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.

 

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

 

Why join Aptiv ?

·       You grow at Aptiv. Aptiv's winning culture is global by design. We bring together diverse perspectives, cultures, and business contexts to solve our customers' toughest challenges. In this environment, every individual can grow, lead, and make an impact, regardless of background, because inclusion fuels how we innovate and win. 

·       You make an impact at Aptiv. One of the strengths of humanity is our drive to progress, to improve, to achieve more tomorrow than we did yesterday. People need solutions they can trust when it matters most. At Aptiv, you are building those solutions every day.

·       You have support at Aptiv. We ensure you have the resources and support you need to take care of your family, your physical health, and your mental health with a competitive benefits package

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

 Meet the Next Generation Aptiv

At Aptiv, we deliver innovative solutions that people trust when it matters most.

Progress is never static. It is about reaching further, exploring new possibilities, and enabling mobility. Aptiv empowers customers to create solutions people rely on—advancing safety and autonomy in Automotive and Commercial Vehicles, enabling mission-critical performance in Aerospace & Defense, and powering intelligent systems across Energy, Enterprise, and Telecommunications. We also drive precision and efficiency in Industrials & Robotics and support life-critical innovation in Medical technologies.

Guided by our winning culture and values to Think & Act Like Owners, as One Team, and Play to Win, we turn commitment into results and achieve more together.

 

Join Us to Deliver Innovative Solutions That People Trust!


Privacy Notice - Active Candidates: https://www.aptiv.com/privacy-notice-active-candidates

Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.

Skills Required

  • 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
  • 5+ years of hands-on experience developing and deploying machine-learning algorithms
  • Strong understanding of supervised learning, deep learning, model evaluation, dataset development, and error analysis
  • Experience with PyTorch and/or TensorFlow
  • 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
  • Experience designing, implementing, or maintaining machine-learning training pipelines
  • Experience with large-scale datasets and data-processing workflows
  • Experience performing root-cause analysis of model failures and performance regressions
  • Experience working with algorithm, software, systems, and validation teams
  • Ability to drive technical initiatives from concept through production deployment
  • Experience developing Transformer-based neural networks
  • Experience with Vision Transformers, multimodal 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 cameras, radar, lidar, ultrasonic sensors, or vehicle signals
  • Experience shipping production ADAS or autonomous-driving features
  • Experience with AWS or cloud-native machine-learning infrastructure
  • Experience with experiment tracking, model registries, automated retraining, model deployment pipelines, or continuous evaluation
  • Experience building scalable machine-learning platforms used by multiple teams
  • Experience with annotation workflows, active learning, synthetic data generation, data-quality metrics, or scenario mining
  • Experience with sensor fusion, probabilistic estimation, Kalman filtering, SLAM, or factor graph optimization

APTIV Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about APTIV and has not been reviewed or approved by APTIV.

  • Retirement Support — A 401(k) plan with company contribution and competitive matching is described as a notable component of the total rewards package. Equity participation and performance bonuses are also positioned as part of long-term and variable compensation.
  • Healthcare Strength — Core coverage is portrayed as broad, spanning medical, dental, vision, life, and disability insurance. Mental health resources and an Employee Assistance Program are also included as part of wellness support.
  • Leave & Time Off Breadth — Paid holidays, paid sick days, and flexible time-off policies are included in the benefits mix. Flexible scheduling and remote-work programs further support time management and personal needs.

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The Company
HQ: Schaffhausen
17,787 Employees

What We Do

Aptiv is a global technology company that develops safer, greener and more connected solutions enabling the future of mobility. #ItsOurMove

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