Role overview
- Develop and evaluate machine learning models for various AI applications, leveraging techniques such as supervised learning, unsupervised learning, and reinforcement learning.
- Conduct thorough model evaluation and validation, including performance metrics analysis, to ensure accuracy, reliability, and robustness.
- Implement and optimize automated machine learning (AutoML) pipelines and frameworks to streamline model development, training, and deployment processes.
- Utilize AutoML tools and techniques to automate feature engineering, model selection, and hyperparameter tuning for improved efficiency and scalability.
- Utilize cloud computing platforms such as AWS, Azure, or Google Cloud to deploy and scale machine learning models and applications.
- Leverage cloud-based services and resources for data storage, processing, and analysis to support AI/ML workflows and pipelines.
- Implement continuous integration and continuous development (CICD) pipelines and practices to automate model deployment, testing, and monitoring.
- Integrate AI/ML solutions into existing CICD workflows, ensuring seamless integration with software development processes.
- Apply knowledge of automotive product development processes and industry standards to design and develop AI/ML solutions for automotive applications.
- Collaborate with cross-functional teams to understand product requirements, specifications, and constraints, ensuring alignment with automotive development practices.
- Design and conduct A/B tests and experiments to evaluate the effectiveness and impact of AI/ML models and algorithms in real-world scenarios.
- Analyze test results and make data-driven recommendations for model improvements and optimizations based on observed performance metrics.
- Develop and orchestrate ML workflows using Kubeflow Pipelines to automate model training, evaluation, and deployment processes in Kubernetes environments.
- Implement continuous integration and delivery pipelines using Jenkins to automate build, test, and deployment tasks for AI/ML projects.
What we're looking for
- Ph.D. in computer science, machine learning or related field. Or, master degree with extensive experience in similar fields with also in ADAS related working experience.
- Excellent analytical skills and a good mathematical background
- Professional experience in at least 2 of the following areas:
- Deep neural networks and other state of the art ML techniques for perception, segmentation, fusion, prediction and planning, or other related applications
- State of the art Reinforcement learning techniques
- Time series prediction with modern ML techniques, such as RNN
- State of the Art (SOTA) ML techniques such as different attention mechanism of transformers, deformable transformer, vision transformer, or similar area.
- Experience in generative model, foundation model, vision-language model (VLM), vision-language-action model (VLA), or related large language model (LLM)
- Systematic, goal and outcome oriented working style
- Professional experience in AI development frameworks PyTorch
- Professional Skills in Python, C++
- English skill both in oral and written
- Experience in handling datasets and data science methods
- Understanding of edge processing / Embedded AI and related methods like RUST is a plus
- Experience in developing software as part of a team and Git, continuous integration tools and an agile development process
- Proven track record of publications in relevant conferences (CVPR, NIPS, ICCV, ICRA, Fusion, and others…) and scientific background on relevant topics
#LI-AW1
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.
Tags & focus areas
Used for matching and alerts on DevFound Ai Ai Engineer Machine Learning