Deep Learning Engineer / LLM, VLM, NLP

About Us:

Retail Robotic Solutions (RRS) stands at the forefront of innovation, merging cutting-edge artificial intelligence (AI) with the dynamic needs of the catering industry. As pioneers in this space, our mission is to transform catering operations globally by making them more efficient, faster, and profoundly cost-effective. Our AI-driven solutions are unrivaled in their recognition capabilities and operational enhancements, setting a new benchmark for excellence in the industry.

At RRS, we don't just innovate; we redefine what's possible, delivering significant cost savings and unparalleled efficiency that set a new industry standard. Our success is evidenced by our strong and growing presence in the European market. As we prepare to expand into the USA market, our commitment to revolutionizing the catering industry remains unwavering.

Proudly affiliated with French Tech and Station F, we operate from their renowned campus, surrounded by a thriving ecosystem of innovation and entrepreneurship. Join us at RRS, where we are not just leading the industry—we are shaping its future.

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Job Summary:

We are looking for a Deep Learning Engineer to work with Vision-Language Models (VLMs). Your core mission will be to design, train, and optimize multimodal AI systems using parameter-efficient fine-tuning (PEFT) and Supervised Fine-Tuning (SFT). You’ll handle end-to-end development: from building Docker-based training pipelines on Google Vertex AI to deploying models into production. This role is ideal for those passionate about cutting-edge AI and solving challenges at the intersection of computer vision and natural language processing.

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Key Responsibilities:

• Model Training:

  • Training and adapting Vision-Language Models (VLM) using LoRA and PEFT (Parameter-Efficient Fine-Tuning).

  • Experience with transformers, TRL, PEFT and langchain libraries

  • Implementing Supervised Fine-Tuning (SFT) to enhance model performance on domain-specific datasets.

  • Configuring and managing training pipelines in Google Vertex AI (distributed GPU training, experiment tracking).

  • Setting tasks for our inner labeling team

• Performance Optimization: Continuously improve the performance of deployed models, optimizing for speed and accuracy.

• Collaboration: Collaborate with software engineers to integrate computer vision models into end-user applications.

• Research: Stay up-to-date with the latest research and advancements in AI. Apply new techniques and methodologies to improve existing solutions.

• Documentation: Create comprehensive documentation for developed models and algorithms, ensuring knowledge transfer and ease of maintenance.

• Problem-Solving: Participate in brainstorming sessions and contribute ideas to project planning.

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Skills and Qualifications:

• Education: Bachelor’s degree in the technical field. A Master’s degree or relevant certifications is a plus.

• Experience:

  • summarily 2 or more years of experience in LLM, VLM or CV, with a proven track record of developing and deploying neural networks. Internships, pet projects and applicable courses are counted.

  • adapting large models (ViT, CLIP, GPT) via LoRA and PEFT (e.g., Hugging Face libraries).

• Technical Skills:

  • Proficiency in Python;

  • Experience with transformers, TRL and PEFT and langchain libraries;

  • Knowledge of model deployment frameworks such as ONNX (onnx runtime), TensorRT;

  • Experience with Google Cloud Platform(Vertex AI.Pipelines) for training NN is a big plus

  • Familiarity with computer vision libraries such as OpenCV, scikit-image is a plus.

  • Basic familiarity with MLOps practices for model monitoring is a plus.

  • Experience with multimodal datasets (text + images) is a big plus.

• Mathematical and Analytical Skills:

  • Deep applied understanding of linear algebra, mathematical analysis, probability theory, statistics, and mathematical optimization related to Deep Learning.

• Soft Skills:

  • Strong problem-solving and analytical skills;

  • Ability to work independently;

  • Willingness to learn and adapt to new technologies and methods.

• Language:

  • English (Professional working proficiency).

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Compensation and Benefits:

• Competitive salary.

• Access to Vertex AI infrastructure (GPU A100/V100) and dedicated resources.

• Professional development opportunities, including conferences and courses.

• Fully remote work + flexible hours.

• Opportunity to work on cutting-edge technology with a talented and dynamic team.

• Relocation to France is negotiable.

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Application Process:

Interested candidates should submit their resume together with motivation letter (optional). If you pass the initial resume screening, you will be invited to two interviews to test your technical skills and alignment with the company's mindset.