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

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.

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

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/

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

• Stron