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Bosch Senior Machine Learning Software Engineer in Sunnyvale, California

Company Description

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 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, manufacturing, enterprise AI, health care, smart home and building, and manufacturing domains.

Our AI systems engineering team is looking for an experienced machine learning software engineer who is passionate about designing 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.

Job Description

  • Work with an international team of engineers and research scientists to deliver AI applications to internal Bosch customers

  • Communicate with various stakeholders to identify requirements for machine learning solutions

  • Evaluate machine learning research prototypes for integration into existing production software systems

  • Contribute to reference architectures and help set best practices for rapidly scaling research innovations

  • Write, test, and review code, contribute to clearing technical debt, and troubleshoot issues to maintain code quality and system performance

Qualifications

Basic Qualifications:

  • Bachelors’ degree in software engineering, computer science, or related field

  • 3+ years of professional software development experience with exposure to the machine learning life cycle

  • Industry experience working on high-impact, customer-facing products or applications

  • Exposure to architecture design of a large scale software application

  • Experience implementing machine learning algorithms

Preferred Qualifications:

  • Masters’ degree in software engineering, computer science, or related field

  • 5+ years of professional software development experience working on a machine learning product

  • Experience in machine learning system architecture design

  • Experience integrating machine learning algorithms into production systems

  • Experience working in an Agile team

  • Experience working with AI researchers and/or industry experience in the manufacturing domain is a plus

Additional Information

The U.S. base salary range for this full-time position is $160,000 - $175,000. Within the range, individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. Your Recruiter can share more details about the specific salary range for this position during the interview process.

In addition to your base salary, Bosch offers a comprehensive benefits package that includes health, dental, and vision plans; health savings accounts (HSA); flexible spending accounts; 401(K) retirement plan with an attractive employer match; wellness programs; life insurance; short and long term disability insurance; paid time off; parental leave, adoption assistance; and reimbursement of education expenses. Learn more about our full benefits offerings by visiting: https://www.myboschbenefits.com/public/welcome . Pay ranges included in the postings generally reflect base salary; certain positions may include bonus, commission, or additional benefits.

By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.

All your information will be kept confidential according to EEO guidelines.

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