The Bosch Research and Technology Center North America, with offices in Sunnyvale, Pittsburgh, and Cambridge, is part of the global Bosch Group, a company with over 70 billion Euro in annual revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) provides innovative technologies in various Bosch business fields such as energy technologies, internet technologies, circuit and advanced MEMS design, semiconductors and wireless, and artificial intelligence.

As a part of the global research organization, our research department in Silicon Valley focuses on scalable and assistive AI. We develop solutions for Bosch products and services in the automated driving, advanced driver assistance systems (ADAS), robotics, enterprise AI, health care, smart home and building, and manufacturing domains.

Our AI systems engineering team is looking for an experienced research engineer who is passionate about improving machine learning systems and building cutting edge AI software applications. Your work will help bridge the gap between research and product, bringing new innovations to Bosch business units at scale.

We Are Bosch.

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our areas of activity are every bit as diverse as our outstanding Bosch teams around the world. Their creativity is the key to innovation through connected living, mobility, or industry.

Let’s grow together, enjoy more, and inspire each other. Work #LikeABosch 

• Reinvent yourself: At Bosch, you will evolve.
• Discover new directions: At Bosch, you will find your place.
• Balance your life: At Bosch, your job matches your lifestyle.
• Celebrate success: At Bosch, we celebrate you.
• Be yourself: At Bosch, we value values.
• Shape tomorrow: At Bosch, you change lives.

• Work with an international team of engineers and research scientists to continuously deliver AI models to internal Bosch customers
• Communicate with various stakeholders to identify requirements for AI infrastructure and machine learning solutions
• Explore and prototype closed loop machine learning system designs
• Implement efficient and production ready solutions to address challenges in development of autonomous driving systems
• Write and test code to improve efficiency of machine learning and data pipelines
• Summarize research findings in high-quality paper and/or patent submissions

Required:

• Bachelor’s or master’s degree in software engineering, computer science, or related field

• Hands-on experience with Azure or other public cloud tooling for machine learning development
• Experience characterizing and improving utilization and performance of machine learning workloads
• Strong software engineering skills in Python and proficiency with libraries such as PyTorch
• Hands-on experience with agentic systems
• Excellent problem-solving skills and attention to detail
• Effective communication and collaboration skills

Preferred:

• 1+ years of professional software development experience working on a machine learning product in the automotive domain
• Experience training machine learning models at scale
• Prior publications in the field of machine learning to relevant academic or industry conferences
• HPC experience a plus

The U.S. base salary range for this position is $160-175k. Within the range, individual pay is determined based on several factors, including, but not limited to, type of degree, work experience and job knowledge, complexity of the role, type of position, job location, etc. Your Hiring Manager can share more details about the specific salary range for this position during the interview process.

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.