AI Engineer / NLP
L-Acoustics · Massy, Île-de-France, France
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- On site
- Full-time
- $120,000 / year
- Massy, Île-de-France, France
Job highlights
- Design and industrialize agent-based and NLP systems.
- Transform generative AI into scalable products.
- Drive agentic vision and AI governance.
- Deploy and monitor NLP models in production.
- Collaborate on AI projects and share innovations.
About the role
AI Engineer NLP
L‑Acoustics is the world leader in premium professional sound systems for live events. From world-class artists on tour, to major music festivals in every genre, to opening and closing ceremonies of planetary sporting events, we are the trusted choice of event professionals who require extreme reliability and fidelity show after show. Designed and manufactured in Europe, and available in 80 countries globally, L-Acoustics employs over 1300 people worldwide, with 20% of team resources devoted to R&D and application. Our products are built to the highest professional and sustainable standards, which we, continue to define and elevate. Within the Data & AI team, you design and industrialize agent-based and NLP systems capable of reasoning, planning, and acting autonomously. Your mission is to transform generative AI technologies into robust, scalable products delivering measurable business value. You drive the agentic vision across the organization and structure governance, performance measurement, and cost control of AI systems.Responsibilities
Scoping & Architecture
- Translate business needs into structured technical specifications
- Design multi-agent architectures and define orchestration mechanisms
- Develop autonomous agents integrated into existing workflows
- Define performance KPIs for agentic systems
- Implement governance frameworks (security, traceability, auditability)
Generative AI & NLP
- Build chatbots and document-based intelligent agents
- Evaluate and implement LLM strategies adapted to use cases: RAG, GraphRAG, Lightweight fine-tuning, Query rewriting
- Manage embeddings, semantic search, and indexing pipelines
- Process structured and unstructured data (PDFs, standards, emails, multilingual corpora)
- Address bias mitigation and cultural adaptation in language models
Industrialization & Performance
- Deploy and monitor NLP models in production (APIs, microservices, CI/CD)
- Implement advanced observability (logs, traces, metrics)
- Optimize large-scale token consumption and cost management
- Ensure data security, GDPR compliance, and access governance
- Rapidly prototype agent workflows to validate technical feasibility before scaling
Collaboration & Leadership
- Work closely with AI Engineers and Data Scientists on: Model selection, Fine-tuning strategies, Evaluation frameworks
- Lead structured technology watch and share innovations internally
- Contribute to technical community engagement, mentoring, and conferences
Qualifications
- Master’s degree (or equivalent) in Computer Science or Artificial Intelligence
- 4–6+ years of experience in AI / NLP (or demonstrable project-based expertise)
- Hands-on experience with hosted or self-managed LLMs
- Practical expertise in embeddings, RAG pipelines, evaluation, and observability
- Proven experience with Azure cloud environments
Skills
- Strong Python expertise (FastAPI, Flask, data tooling)
- Proficiency in C# or C++ for complex AI applications
- REST API architecture, SDKs, and system integration
- Agent orchestration frameworks (e.g., LangChain or equivalent)
- HuggingFace, MLflow, and open-source AI tooling
- Advanced PostgreSQL (SQL)
- Docker and containerization
- Azure ecosystem: Cognitive Services, AI Foundry, Azure Search
- Knowledge of GCP or AWS is a plus
- Solid MLOps / LLMOps culture (versioning, reproducibility, environment management)
Must Have
- Proficiency in Python for developing computer vision algorithms.
- Knowledge of deep learning frameworks (PyTorch, TensorFlow).
- Ability to read and understand scientific articles in English.
Nice to Have
- Azure IaaS infrastructure expertise
- Team leadership or Tech Lead experience
- End-to-end AI solution delivery (scoping, estimation, development, audit, optimization)
- Voice AI / TTS technologies
- Microsoft AI-102 – Azure AI Engineer Associate certification
Soft Skills
- Structured technological curiosity
- Ability to explain complex AI concepts to non-experts
- Autonomy and rigor
- Strong product mindset and business impact orientation
- Collaborative mindset
What We Offer
At L-Acoustics, newcomers are welcomed into a dynamic and inclusive environment that blends technological excellence with human-centered values. New team members benefit from the following:- Hybrid work model with up to 2 remote workdays per week
- Comprehensive health benefits to support you and your family.
- Opportunities for internal mobility and career advancement
- A collaborative, international work environment driven by innovation.
- Employee events and initiatives that foster community and creativity.
- Access to the company’s CSE (Comité Social et Économique), offering cultural, leisure, and social benefits.
- A strong focus/emphasis on work-life balance
Key skills/competency
- AI Engineer
- NLP
- Generative AI
- LLM
- Python
- Azure
- MLOps
- RAG
- Embeddings
- Agent Orchestration
Skills & topics
- AI Engineer
- NLP Engineer
- Generative AI
- LLM
- Python
- Azure
- MLOps
- RAG
- Embeddings
- Agent Orchestration
- Data Scientist
- Artificial Intelligence
- Machine Learning
- Speech Recognition
- Natural Language Processing
- Computer Vision
- Deep Learning
- PyTorch
- TensorFlow
- FastAPI
- Flask
- LangChain
- HuggingFace
- MLflow
- PostgreSQL
- Docker
- Microsoft Azure
- Cognitive Services
How to get hired
- Tailor your resume: Highlight AI/NLP experience, LLM expertise, and Azure cloud skills.
- Showcase projects: Include details on RAG pipelines, embeddings, and agent orchestration.
- Demonstrate Python proficiency: Emphasize FastAPI, Flask, and data tooling experience.
- Prepare for technical questions: Brush up on LLMs, MLOps, and Azure AI services.
- Highlight soft skills: Be ready to discuss product mindset and collaboration.
Technical preparation
Master Python for AI and data tooling.,Practice with LLMs, RAG, and embeddings.,Familiarize with Azure AI services.,Understand MLOps and CI/CD pipelines.
Behavioral questions
Explain complex AI to non-experts.,Describe product mindset and business impact.,Share experience with structured curiosity.,Discuss collaborative and autonomous work.
Frequently asked questions
- What are the key technical skills required for the AI Engineer NLP role at L-Acoustics?
- The AI Engineer NLP role at L-Acoustics requires strong Python expertise (FastAPI, Flask), proficiency in C# or C++, experience with agent orchestration frameworks (like LangChain), HuggingFace, MLflow, advanced PostgreSQL, Docker, and the Azure ecosystem (Cognitive Services, AI Foundry, Azure Search). Familiarity with GCP or AWS is a plus. A solid MLOps/LLMOps culture is also essential.
- Does L-Acoustics offer remote work options for this AI Engineer NLP position?
- Yes, L-Acoustics offers a hybrid work model for this AI Engineer NLP position, allowing up to 2 remote workdays per week. This provides a balance between in-office collaboration and remote flexibility.
- What kind of projects can I expect to work on as an AI Engineer NLP at L-Acoustics?
- As an AI Engineer NLP at L-Acoustics, you will design and industrialize agent-based and NLP systems, transform generative AI technologies into scalable products, build chatbots and intelligent agents, manage embeddings and semantic search, and deploy/monitor NLP models in production. You'll focus on delivering measurable business value through AI.
- What educational background is preferred for the AI Engineer NLP role at L-Acoustics?
- L-Acoustics prefers candidates with a Master’s degree (or equivalent) in Computer Science or Artificial Intelligence for the AI Engineer NLP role. However, demonstrable project-based expertise in AI/NLP is also considered valuable.
- How does L-Acoustics support professional development for its AI Engineers?
- L-Acoustics supports personal and professional development through various means, including opportunities for internal mobility and career advancement, a collaborative international work environment, and access to the company's CSE for cultural, leisure, and social benefits. They foster an environment where employees are empowered to grow and contribute.
- What is the required experience level for the AI Engineer NLP position?
- The AI Engineer NLP position at L-Acoustics typically requires 4-6+ years of experience in AI/NLP. Demonstrable project-based expertise in these areas can also be considered.
- What are the core responsibilities of an AI Engineer NLP at L-Acoustics?
- Core responsibilities include translating business needs into technical specifications, designing multi-agent architectures, developing autonomous agents, implementing AI governance, evaluating and implementing LLM strategies, managing embeddings and semantic search, deploying NLP models, and collaborating with other AI professionals.