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AI/ML Intern, Long-Term Memory & Multimodal SLMs for Automotive Agents

San Jose, Vereinigte Staaten von Amerika

Actively hiring, first seen by us 9 days ago
Pay
Pay not listedSimilar roles state $166K–$240K
Work setting
Not stated
Employment
Not stated

Before you apply

New graduates
For current studentsJob title: AI/ML Intern, Long-Term Memory & Multimodal SLMs for Automotive Agents

What you’ll work on

Full posting
  • 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

From the employer’s posting
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.

What you’ll bring

All qualifications

Core experience

  • 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

Preferred experience

  • Hands-on experience with Liquid AI models (LFM2.5, LFM3)
Qualification wording
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)
Education & alternatives
Minimum Qualifications: - Master's or higher degree, in CS/CE/EE, Math, Statistics, or related fields - Python and PyTorch; Git-based workflows
Apply at Mercedes-Benz Group

Posting record

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Actively hiringFirst seen by us 9 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 4, 20269 days ago
Recorded sightings
11
Last seen by us
Nov 14, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

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.

Time since we first saw it

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.

Mercedes-Benz Group is hiring

17 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Hugging Face
  • PyTorch
  • Transformers
Where the posting names them
- 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)

Your next step

Complete your application on jobs.mercedes-benz.com. The employer’s form will show what is required.

Already applied? Track this application

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 612, the most 1,081, and the latest week had 1,068.
August 17Last week

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.

About the role

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.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

Aufgaben

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.

Qualifikationen

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.

PRIVACY NOTICE FOR CALIFORNIA RESIDENTS

https://mbrdna.com/california-employee-privacy-notice/

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San Jose, Vereinigte Staaten von Amerika

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