Senior AI Engineer

About the role

The company is looking for a Senior AI Engineer with a proven record of designing, developing and deploying advanced AI solutions to real-world problems. You will lead the full lifecycle of AI projects, from research and prototyping to production-grade systems, including solutions running on workstations and edge or physical AI platforms.

Key responsibilities

• Design, train and optimize AI models across machine learning, deep learning, reinforcement learning, NLP, computer vision and generative AI
• Build and fine-tune Transformer-based architectures, diffusion models and large language models
• Design agentic AI systems and AI workflows, including orchestration, tool use and multi-step reasoning pipelines
• Scale AI proofs of concept into robust, maintainable product-level solutions
• Optimize models for efficient inference through quantization, pruning, distillation and hardware-aware tuning
• Deploy AI on GPU workstations and edge or embedded platforms, including physical AI applications
• Run benchmarking and testing frameworks and integrate models with existing systems, APIs and enterprise infrastructure
• Collaborate with product, data, software and domain teams, mentor junior engineers and stay current with AI research

Required profile

• Bachelor's degree in Computer Science, Artificial Intelligence or a related field; a Master's or PhD in AI, ML or data science preferred
• Proven, documented experience designing, developing and deploying advanced AI solutions, with a track record of moving projects from PoC to production
• Strong problem-solving, communication and technical leadership skills
• Publications, patents or open-source contributions are a plus

Required skills

• AI domains: supervised and unsupervised learning, CNNs, Transformers, NLP, computer vision, LLMs, diffusion models, agentic AI and RAG
• Optimization: quantization, pruning, distillation, transfer learning and efficient fine-tuning (LoRA, PEFT)
• Frameworks: PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers, ONNX, OpenCV
• GPU and edge: CUDA, TensorRT, ONNX Runtime, OpenVINO, NVIDIA Jetson or similar
• Deployment: REST/gRPC APIs, Docker, Kubernetes, CI/CD, MLOps, cloud platforms (AWS, Azure, GCP) or on-premises
• Advantageous: data science, data engineering, sensor integration, robotics and simulation

What we offer

• Competitive compensation and benefits
• Work on impactful, cutting-edge AI projects
• Professional development and career growth