Research Engineer – Multi-modal AI systems

Company Description

The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania and Cambridge, Massachusetts is a part of the global Bosch Group /home/bou1pi/workspace/active-learning-toolchain/actlearn/training/config/model/frontend/gabor.yaml (www.bosch.com), a company with over 90 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America provides technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence (for example, human-assisted AI, natural language processing, robotics, 3D perception, and AI platform), energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design.

The Bosch Research and Technology Center in Pittsburgh, PA is focused on the research and development of cutting-edge AI and sensing technologies that will shape the future of the company's products. This position is part of an ambitious effort to design and develop intelligent multi-modal sensing at the intersection of deep learning and signal processing, with diverse application domains ranging from physical security to intelligent and connected vehicles.

Job Description

Originating from Bosch AI research in Pittsburgh, we are responsible for pushing the boundaries of signal sensing and multimodal models through key innovations to solve complex industry problems and shape the future of Bosch products and services for both internal and external users. We work with internal partners of different Bosch business units to transfer our solutions into future products. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals.

In this position, you are expected to:

• Become the engineering multiplier of a research team, by streamlining the software workflow of different AI/ML research projects.
• Define and maintain good software engineering and documentation practices in the team, coordinate reviews and maintenance of our codebase, coordinate contributions from different projects.
• Run large-scale AI experiments in coordination with the team, aiding researchers in validating ideas and prototypes across a variety of public and private datasets.
• Maintain software tools that the team delivers to other units, fix bugs, provide support, discuss with the team missing functionalities and propose future developments grounded in business needs.
• Optimize existing models and data pipelines, deploy AI models for proof-of-concept or studies.

Qualifications

Basic Qualifications

• MS degree or higher with 3+ years of industry experience after graduation on multimodal sensor fusion.
• Proficiency with Python, PyTorch (including libraries such as torchaudio, torchvision, torchmetrics), PyTorch Lightning, dependency management software (Poetry), version control systems (Git), pre-commit, linting, CI/CD workflows, containerization (Docker), MLOps on public cloud infrastructures (Azure), integrated development environment (VSCode or PyCharm) and experiment tracking tools (MLFlow).
• Familiarity with high-performance computing (HPC) systems and job schedulers (Slurm, LSF).
• Strong interpersonal, communication, and teamwork capabilities.

Preferred Qualifications

• 5+ years of experience in industrial research and productization.
• Familiarity with container orchestration systems (Kubernetes).
• Hands-on experience in product development in the above-mentioned areas for consumer/enterprise markets.

Additional Information

Equal Opportunity Employer, including disability / veterans.  

*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.