Senior ML/AI Engineer

A Senior ML/AI Engineer is needed for a full-time position (40 hours per week) in Europe. The role supports AI innovation and acceleration for business units and develops computer-vision and generative-AI solutions, with an emphasis on device inference, primarily on Qualcomm chipsets. Researchers create and fine-tune models before handing them to the engineering team for optimization, quantization, and application-solution development with customers.

The ideal candidate is a hands-on Machine Learning Engineer who can work independently and collaboratively on LLM/NLP-focused tasks. The role requires practical model-development and engineering experience, including data preparation, experimentation, version control, and deployment in a remote team environment.

Requirements

• Proficient Python skills
• Excellent problem-solving and analytical abilities
• Solid understanding of machine learning and AI
• Hands-on experience with classification and retrieval tasks
• Experience with large language models, including fine-tuning, retrieval-augmented generation, foundation model APIs, and prompt engineering
• Proficiency in Pandas and NumPy
• Strong knowledge of NLP concepts
• Familiarity with Hugging Face Transformers and Datasets
• Knowledge of Faiss or comparable nearest-neighbor search tools
• Experience with Hydra for configuration management
• Experience using Weights & Biases for experiment tracking
• Proficiency with Git and GitHub
• Excellent data management and manipulation skills
• Experience collaborating on shared codebases and remotely with teams and servers

Nice to have

• Understanding of vector search and embedding-based retrieval
• Familiarity with LLM evaluation and optimization
• Knowledge of MLOps practices
• Experience deploying ML models in production environments
• Experience with cloud-based ML infrastructure
• Familiarity with LangChain, LlamaIndex, or similar LLM frameworks

Responsibilities

• Develop, train, evaluate, and deploy machine learning models
• Work on classification, retrieval, NLP, and LLM-based tasks
• Build and optimize retrieval-augmented generation workflows
• Create fine-tuned large language models for specific use cases
• Use foundation model APIs and apply prompt-engineering techniques
• Prepare, clean, manage, and manipulate datasets for ML model development
• Use Pandas and NumPy for data analysis and preprocessing
• Work with Hugging Face Transformers and Datasets libraries
• Apply Faiss or similar tools for efficient nearest-neighbor search and retrieval tasks
• Use Hydra for configuration management
• Use Weights & Biases or similar tools for experiment tracking
• Collaborate with team members on shared codebases and remote projects
• Use Git and GitHub for version control and collaborative development
• Work on remote servers to develop, test, and deploy machine learning models

Benefits

• US and EU projects based on advanced technologies
• Competitive compensation based on skills and experience
• Regular performance appraisals to support growth
• Flexible workspace: remote or office
• Bonuses for article writing, public talks, and other activities
• Generous time off, including vacation, national holidays, sick leave, and family days
• Personalized learning programs tailored to interests and skill development
• Free technical webinars and meetups
• Regular corporate online activities
• Friendly, supportive team community