below marketmost similar roles pay hereabove market
This role pays less than
75%
of similar roles. Most pay
$176,100–$246,968
— the blue band above.
At the midpoint, this role pays about
$175k
versus about
$212k
for comparable roles.
Based on 240 similar postings.
Employer
About Bosch
Bosch is a global engineering and technology company supplying mobility solutions, industrial technology, consumer goods, and energy and building technology; Robert Bosch LLC is its North American arm.
Bosch currently has
66 open roles
on FindRole.
Listed pay typically runs
$165,000–$185,000
across 31 roles with salary data.
The AI Research Scientist - Safety joins the Foundation Model Powered AI Enablers group to lead strategic research and engineering initiatives regarding AI safety, alignment, and model reliability. This role focuses on developing generative world models, simulation frameworks, and physical reasoning techniques to evaluate complex driving edge cases for ADAS feature releases and autonomous systems. Key responsibilities include implementing out-of-distribution detection, failure mode analysis, and uncertainty estimation while transferring machine learning algorithms into production pipelines. The candidate must possess a Ph.D. and expertise in self-supervised learning or generative dynamics. Required technical skills include Python, PyTorch, or JAX, with preferred proficiency in C++ and distributed training. The work addresses the technical challenge of ensuring robust, trustworthy AI behavior within industrial, mobility, and autonomous driving domains.
Lead strategic research and engineering initiatives in AI safety, alignment, and model reliability for autonomous systems.
Advance generative world models and simulation frameworks to evaluate complex driving edge cases.
Transfer cutting-edge safety frameworks and machine learning algorithms into operational production pipelines.
Implement rigorous safety validation, out-of-distribution detection, and uncertainty estimation methods.
Monitor emerging developments in foundation models and represent the organization at top-tier research conferences.
Provide expert technical counsel to senior leadership on R&D roadmaps and patent portfolio growth.
What we're looking for
Ph.D. in Computer Science, Machine Learning, Robotics, Artificial Intelligence, or a related quantitative field.
3+ years of dedicated research experience in world models, generative dynamics, self-supervised learning, or physical reasoning for autonomous systems.
2+ years of industrial R&D experience creating, fine-tuning, and deploying large-scale machine learning models and safety-critical algorithms into production.
Hands-on engineering proficiency in Python and deep learning frameworks like PyTorch or JAX.
Deep theoretical and practical expertise in AI safety techniques, including alignment, adversarial robustness, interpretability, and uncertainty quantification (preferred).
Strong low-level engineering experience with C++ and high-performance distributed training pipelines (preferred).
Proven track record of peer-reviewed publications in top-tier machine learning or robotics venues (preferred).
Demonstrated experience generating intellectual property and securing patent contributions in trustworthy AI or autonomous systems (preferred).