Senior AI/ML Engineer - NLP / LLM / GenAI (f/m/d)

Position Description

As a Senior AI/ML Engineer at Cinemo, you will play a key role in researching, developing, and bringing GenAI / LLM / NLP capabilities into production to elevate the in-car experience for intelligent cockpit systems. You will design and evolve both models and the underlying software architectures (e.g., AgenticAI frameworks) to ensure non-deterministic GenAI systems are safe, robust, and scalable—from cloud-based deployment to integration on automotive products running Android Automotive OS (AAOS) and Linux.

You will combine hands‑on ML engineering with system‑level thinking: building reliable agent workflows, automating evaluation and benchmarking, implementing guardrails, and continuously advancing the GenAI stack as the field evolves—bridging cloud services and embedded, in‑vehicle constraints.

In this role, you will:

• Lead GenAI / LLM / NLP research, development, tuning, and deployment for intelligent cockpit and infotainment experiences.
• Design, implement, and operate production‑grade AgenticAI frameworks (tool use, planning, memory, orchestration) within Cinemo’s middleware architecture.
• Build and run cloud-based services and pipelines for scalable deployment, monitoring, and continuous improvement of GenAI systems.
• Develop prompt engineering strategies and guardrailing mechanisms to meet automotive‑grade requirements (safety, policy, latency, cost, quality).
• Establish automated evaluation and benchmarking for non‑deterministic systems (offline/online evaluation, regression testing, A/B testing).
• Collaborate across teams to connect cloud GenAI capabilities with in‑vehicle environments across diverse automotive hardware and OS platforms.

What you will need to succeed:

• PhD or M.Sc. in Computer Science, Machine Learning/AI, Data Science, Computational Linguistics, Electrical Engineering, Robotics, or a closely related field.
• Strong experience in NLP, Machine Learning, Deep Learning, and data preprocessing in production‑oriented environments.
• Proven expertise with Transformer architectures and modern LLM ecosystems, including adaptation and evaluation for real‑world applications.
• Experience with AgenticAI concepts and agent frameworks (e.g., orchestration patterns, tool calling, retrieval, planning) and how to evaluate them.
• Experience deploying and operating ML/GenAI systems in cloud‑based infrastructures (e.g., containerization, CI/CD, monitoring, scalable services).
• Proficiency in Python and common ML frameworks (PyTorch, TensorFlow, Keras) with strong written and spoken English communication skills.