Senior Machine Learning Engineer

What makes this role stand out

• Work at the intersection of cutting-edge AI research and real-world delivery, helping turn GenAI capabilities into production-ready products and business value.
• Build ML/LLM pipelines; integrate, evaluate, and optimize models and agents.
• Apply deep learning, NLP, or CV expertise in hands-on GenAI and LLM work.
• Use techniques such as fine-tuning, prompting, quantization, and LoRA to adapt models for production.

Why it’s worth it

• Work with LLMs, agentic frameworks, MCP-based integrations, RAG, inference optimization, and fine-tuning.
• Build production models and agents that reach real users, rather than only proofs of concept.
• Collaborate with Data Scientists, Software Engineers, and MLOps specialists to deliver end-to-end AI solutions.

Project examples

• Train multimodal LLMs with molecular embeddings as a chemical modality.
• Build AI voicebots that double conversion rates.
• Deliver applied research and performance-optimization projects, including multi-hydrophone underwater sound recognition.
• Build AI systems and training pipelines for drug discovery, AI security, and intelligent agentic platforms.

The ideal candidate

• Has 5+ years of ML engineering experience and experience working with models in production environments.
• Has strong software engineering fundamentals for designing clean architectures and cloud-native solutions in the Python ecosystem.
• Brings hands-on expertise with Large Language Models (LLMs) and Generative AI, including RAG systems, agentic workflows, model integration, and inference optimization for latency, cost, and scalability.
• Has experience designing and implementing AI agents and orchestrating multi-step LLM systems with LangChain, LlamaIndex, DSPy, and MCP-compatible ecosystems.
• Can design and implement end-to-end ML/LLM pipelines, from data preparation and fine-tuning to production-grade APIs and agent-based applications.
• Has solid foundations in machine learning frameworks and deep learning libraries, including PyTorch, scikit-learn, TensorFlow, and Hugging Face.
• Has experience with at least one public cloud platform—AWS, GCP, or Azure—and its AI/ML services.
• Knows how to deploy and monitor models and AI systems, including model CI/CD, logging, observability, and quality monitoring.
• Communicates clearly and collaborates effectively with technical and business/client teams.

Nice to have

• GenAI evaluation and observability experience with LangSmith, Ragas, Phoenix, or Braintrust.
• Vector database and retrieval-system experience with Pinecone, FAISS, Weaviate, or Qdrant.
• Ability to analyze scientific papers and combine insights with original ideas.
• Prompt-engineering experience and experience building simple AI user interfaces with Streamlit or Gradio.
• Experience using AI coding assistants such as Claude Code, Codex, Cursor, or Windsurf, including awareness of their limitations, risks, and best practices.

We offer

Impactful AI projects

• Tackle industry-grade challenges, from LLMs for drug discovery to GenAI on edge devices, AI voicebots, and open-source initiatives.
• Collaborate directly with AI ecosystem partners for early access to tools, production testing, and applied know-how.
• Contribute to open-source initiatives such as ragbits.

Growth & Knowledge Sharing

• Join AI specialists who share expertise through Tech Talks, workshops, and internal training.
• Present work at conferences, run experiments, and stay current with emerging technology.
• Choose a career path and receive development support.

Flexibility & Culture

• Work fully remote, from offices, or from coworking spaces.
• Flexible working hours.
• Burnout-prevention culture and support for work-life balance.
• Onboarding with a buddy from day one.
• High-end equipment, including laptops, dual monitors, and professional peripherals.
• Access to an AI development suite including ChatGPT, Claude, Gemini Advanced, GitHub Copilot, Cursor AI IDE, Claude Code, NotebookLM, and emerging AI tools.
• Agile teams, fast decision-making, and space to experiment.

Basic Benefits

• Private medical care and a Multisport card.
• Company library, onsite English lessons, and a dedicated training budget.
• Free team lunches, fresh fruit, and snacks.
• Team-building activities and holiday celebrations.