Senior Machine Learning Engineer

Svitla Systems Inc. is looking for a Senior ML Engineer for a full-time position (40 hours per week) in Europe or Ukraine

Our client is an American mobile computing company. They provide AI innovation and acceleration for the company's Business Units and are working on CV and GenAI solutions with an emphasis on device inference (Mostly Qualcomm chipsets). Researchers create/fine-tune models and hand them over to the engineering team to optimize, quantize, etc. The team then builds an application solution with customers to demonstrate value.

The perfect candidate should have strong Python programming skills, hands-on experience with data manipulation, and a solid background in machine learning, particularly in classification and retrieval tasks. This role requires practical experience with large language models, NLP, retrieval-augmented generation, prompt engineering, and modern ML development tools.

Requirements

• A solid background in machine learning, particularly in classification and retrieval tasks, as well as hands-on experience with large language models (LLMs), including fine-tuning for specific use cases, retrieval-augmented generation (RAG), foundation models APIs, and prompt engineering.
• Strong understanding of programming with Python.
• Experience with: LLM fine-tuning, retrieval-augmented generation, foundation model APIs, prompt engineering.
• Solid knowledge of machine learning and artificial intelligence.
• Experience with classification and retrieval tasks.
• Hands-on experience with large language models.
• Knowledge of Pandas and NumPy.
• Good understanding of NLP concepts.
• Familiarity with Faiss or similar nearest-neighbor search tools.
• Experience with Hydra for configuration management.
• Experience with Weights & Biases for experiment tracking.
• Experience with Git and GitHub.
• Expertise in data management and manipulation.
• Strong problem-solving and analytical abilities.
• Experience working with shared codebases, remote teams, and remote 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 Python libraries such as 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.