Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
San Jose, Vereinigte Staaten von Amerika
Actively hiring, first seen by us 9 days agoJob title: AI/ML Intern, Long-Term Memory & Multimodal SLMs for Automotive Agents
Design and implement multimodal long-term memory (RAG) for in-vehicle agents
Fine-tune LFM3 and other small language models with SFT and LoRA/QLoRA
Build trigger-based activation from cabin and vehicle signals
Build classifiers for turn detection, PII detection, and intent routing
Optimize and profile models for on-device deployment via quantization and distillation
Design and implement multimodal long-term memory (RAG) for automotive agents in resource-constrained in-vehicle environments.
Fine-tune LFM3 models, especially LFM3-Omni-2B, and other small language models for memory, preference extraction, and function calling (SFT, LoRA/QLoRA).
Build trigger-based activation from multimodal cabin and vehicle signals
Build classifiers for turn detection, PII detection, and intent routing.
Optimize and profile models for on-device deployment (quantization, distillation) on in-vehicle hardware.
Master's or higher degree, in CS/CE/EE, Math, Statistics, or related fields
Python and PyTorch; Git-based workflows
Familiarity with reinforcement learning for language models (DPO, GRPO, or PPO)
Familiarity with multimodal models (text, image, video, and audio)
Familiarity with decision models and classifiers (e.g., calibrated decision models such as LFM3 d1) RAG, embedding models, and vector search
Hands-on experience with Liquid AI models (LFM2.5, LFM3)
Minimum Qualifications: - Master's or higher degree, in CS/CE/EE, Math, Statistics, or related fields - Python and PyTorch; Git-based workflows
Actively hiringFirst seen by us 9 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Day 9
Similar jobs usually come down between day 8 and day 76.
At Mercedes-Benz Group, jobs usually come down by about day 28.
From 5,460 similar postings that came down, and 79 of Mercedes-Benz Group’s. Coming down is not always a hire.
17 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Master's or higher degree, in CS/CE/EE, Math, Statistics, or related fields - Python and PyTorch; Git-based workflows - Fine-tuning small language models (Hugging Face Transformers, TRL, PEFT, LoRA/QLoRA)
- Python and PyTorch; Git-based workflows - Fine-tuning small language models (Hugging Face Transformers, TRL, PEFT, LoRA/QLoRA) - Familiarity with reinforcement learning for language models (DPO, GRPO, or PPO)
Complete your application on jobs.mercedes-benz.com. The employer’s form will show what is required.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
At Mercedes-Benz Research & Development North America (MBRDNA), we are committed to delivering world-class automotive technologies that push the boundaries of what is possible. Our teams of highly skilled engineers and designers use cutting-edge software and technology, to enhance the driving experience and reduce environmental impact.
Position Overview
This internship will start in January of 2027.
The Mercedes-Benz AI Experiences department is seeking an AI/ML Intern for Spring and Summer 2027 (both terms) to join the MB.Intelligence Context team. You will build on-device long-term memory for automotive agents using small language models (SLMs), Liquid AI's multimodal LFM3-Omni model (text, image, video, and audio inputs), and trigger-based activation, helping deliver personalized, privacy-preserving experiences in Mercedes-Benz vehicles.
Job Responsibilities:
Design and implement multimodal long-term memory (RAG) for automotive agents in resource-constrained in-vehicle environments.
Fine-tune LFM3 models, especially LFM3-Omni-2B, and other small language models for memory, preference extraction, and function calling (SFT, LoRA/QLoRA).
Apply reinforcement learning (e.g., DPO, GRPO) to improve memory, activation, and tool-use decisions.
Build trigger-based activation from multimodal cabin and vehicle signals, using decision models (e.g., LFM3 d1-omni-2B) and lightweight classifiers.
Build classifiers for turn detection, PII detection, and intent routing.
Optimize and profile models for on-device deployment (quantization, distillation) on in-vehicle hardware.
Build evaluation frameworks for memory, retrieval, and trigger accuracy, and present findings to Mercedes-Benz teams.
Minimum Qualifications:
Master's or higher degree, in CS/CE/EE, Math, Statistics, or related fields
Python and PyTorch; Git-based workflows
Fine-tuning small language models (Hugging Face Transformers, TRL, PEFT, LoRA/QLoRA)
Familiarity with reinforcement learning for language models (DPO, GRPO, or PPO)
Familiarity with multimodal models (text, image, video, and audio)
Familiarity with decision models and classifiers (e.g., calibrated decision models such as LFM3 d1)
RAG, embedding models, and vector search
Model optimization (quantization, distillation) and ML evaluation methodology
Strong collaboration and written communication skills
Preferred Qualifications:
Hands-on experience with Liquid AI models (LFM2.5, LFM3)
Edge LLM inference (llama.cpp, LiteRT, ExecuTorch, ONNX Runtime)
Privacy-preserving ML, agentic AI/MCP, or Android embedded systems
Always-on perception (wake-word, voice activity, or audio/visual event detection)
This position may involve access to export-controlled technology, hardware, or software under the Export Administration Regulations (EAR), 15 C.F.R. Parts 730-774 and possibly technical data, defense articles and defense services subject to the International Traffic in Arms Regulations (ITAR), 22 C.F.R. Parts 120-130. As such, Mercedes-Benz Research & Development North America may be required to obtain an export license or authorization in accordance with United States law.
Why should you apply?
Here at MBRDNA, you create digital ecosystems around cars, you design a language between humans and machines, you make a car even more intelligent - you make the new reality for cars. MBRDNA was honored as one of the "Best Places to Work" by BuiltIn in January 2024, a testament to our commitment to creating an exceptional work environment. At each of our offices, we foster a culture of collaboration and continuous learning, ensuring every team member can thrive and innovate.
Benefits for Full-Time* Employees Include:
• Medical, dental, and vision insurance for employees and their families
• 401(k) with employer match
• Up to 15 company-paid holidays
• Paid time off (flexible time off for salaried employees), sick time, and parental leave
• Tuition assistance program
• Wellness/Fitness reimbursement programs
* Internships & Contractors excluded from Full-Time Employee benefits
Additional Information:The current hourly rate for this position is as follows and may be modified in the future: $28 (Undergraduate Students)/$32 (Graduate Students)
MBRDNA is an equal opportunity employer (EOE) and strongly supports diversity in the workforce. MBRDNA only accepts resumes from approved agencies who have a valid Agency Agreement on file. Please do not forward resumes to our applicant tracking system, MBRDNA employees, or send to any MBRDNA location. MBRDNA is not responsible for any fees or claims related to receipt of unsolicited resumes.
Mercedes-Benz Research and Development North America, Inc.
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San Jose, Vereinigte Staaten von Amerika
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