AI Research Scientist - GenAI at Bosch Group
Pittsburgh, PA
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Jul 21, 2026
Pittsburgh, PA
Jul 23, 2026
What this job asks for AI summary
A research scientist role focused on multimodal foundation models, agentic AI, and efficient generative AI within Bosch's Pittsburgh AI research group. Day-to-day work involves conducting original research, transferring innovations into Bosch products across manufacturing, ADAS, and smart building domains, and publishing findings at top-tier academic venues. Best suited to candidates with a strong publication record and deep hands-on experience in large model development and deployment.
Senior level · 4+ years · Pittsburgh, PA · Master's required · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 130 people in the Pittsburgh, PA area plausibly meet what this posting asks for (data scientists). range 25–190
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $98,796 (middle half $74,401–$130,048).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (9)
The role is a research scientist position focused on multimodal foundation models and GenAI; 15-2051 (Data Scientists) is the closest SOC match, though the heavy AI/ML research orientation could also fit 15-1299 (Computer Occupations, All Other).
Degree requirement: the JD accepts a Master's degree with 3+ years of relevant industry experience as an alternative to a Ph.D. — minimum hard-required degree is therefore Master's.
The 4+ years of research experience requirement is stated at the role level (not tied to a specific named technology) and is set as the overall years minimum.
The JD requires in-depth experience in foundation models across 'at least two' of several listed areas (time-series data analysis, LLMs, VLMs/MMLMs, inference efficiency, deployment of large models, robustness). All named technologies are captured as required skills since the section is under Basic Qualifications, though in practice only two need to be demonstrated.
Python and C++ are listed as interchangeable examples ('e.g., Python, C++') under a required proficiency statement; Python is the primary with C++ as an alternative.
'AI libraries' is mentioned as a required hands-on experience but names no specific library, so it is omitted per the no-generic-concepts rule.
Math/statistics and computational modeling appear only under Preferred Qualifications.
No compensation figures are provided in the posting.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): time-series data analysis, computational modeling.
Read the full posting
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