Early career Data Scientist / AI Engineer - LLMs & Machine Learning

Data Scientist - AI Engineer — LLMs & Machine Learning

Why join us

There is significant room to contribute your own ideas, own meaningful projects and grow into broader technical responsibility as the product develops.

Build the intelligence behind a recruitment platform.

We are an early-stage AI startup helping recruitment firms identify potential clients earlier, win more business, and grow revenue. Our MVP is ready, with test users already involved. Our ambition goes further: we’re building a full recruitment platform combining hiring intelligence, applicant tracking and client relationship management.

We’re looking for an ambitious, early-career Data Scientist / AI Engineer with strong Python skills, a solid understanding of machine learning and practical experience with large language models.

You should be eager to grow, ready to take ownership, experiment independently, and turn ideas into working product features. We value what you have built, your curiosity and your drive to help build a startup from the ground up.

What you’ll work on

• Build LLM-powered workflows that analyse company news, financial reports and other business information to identify potential hiring needs.
• Develop systems for extracting, classifying and validating information from unstructured text.
• Build retrieval-augmented generation (RAG) pipelines using embeddings, vector databases and relevant source material.
• Develop and evaluate models for scoring hiring signals, ranking opportunities and personalising recommendations.
• Create datasets, run experiments and measure model quality, accuracy and business relevance.
• Work closely with our full-stack developer to bring AI capabilities into the product.
• Help shape our AI architecture and decide when to use LLMs, traditional machine learning or simpler data-driven approaches.

What we’re looking for

• Strong Python skills and experience with Pandas, NumPy and scikit-learn.
• A solid foundation in machine learning, statistics and model evaluation.
• Experience with PyTorch or TensorFlow.
• Practical understanding of LLMs, NLP, prompt engineering and structured outputs.
• Familiarity with embeddings, vector databases and semantic search.
• Experience using tools such as Hugging Face, LangChain or equivalent frameworks.
• Ability to clean and analyse messy data, design experiments and explain your findings.
• An independent, curious mindset and a willingness to take responsibility for your work.
• Working proficiency in English and availability to work on-site in Riga.

Useful extras

• Experience building RAG applications, AI agents or conversational systems.
• Familiarity with fine-tuning, open-source models and inference optimisation.
• SQL, APIs, Git, Docker or experience deploying ML models.
• Personal projects, research or a GitHub portfolio demonstrating your work.

To apply, send your CV and examples of your work. Tell us about an AI or ML project you built, the problem it solved and how you evaluated the results.