Skills, Knowledge and Expertise

We're looking for someone with strong experience building and deploying machine-learning-based data systems, who's ready to take that expertise into a high-impact customer-facing role. You should be comfortable working with the core building blocks of these systems rather than just on top of them.

A machine learning or data science background is valuable, you'll have first-hand experience of the problems our customers are wrestling with. Candidates who have combined experience across data engineering and data science would be ideal, but while we don't expect everyone to tick every box below, deep experience in either machine learning or data engineering is essential.

Machine Learning / Data Science Focus

• Proven experience deploying NLP systems or LLM-powered features into production
• Familiarity with recommendation and retrieval systems, retrieval-augmented generation (RAG) and vector databases.
• Practical experience building or debugging LLM-driven workflows, with opinions grounded in experience of production workflows.
• Demonstrable experience designing and running model evaluation and monitoring frameworks; offline metrics, online performance tracking.
• Hands-on experience fine-tuning transformer-based models for domain- or task-specific use cases, including data preparation, training, and validation.
• Proven track record of building evaluation datasets or benchmarks from scratch - task design, annotation guidelines, quality control, and interannotator agreement.

Data Engineering Focus

• Comfortable moving between different architectural approaches for storing and accessing the data we produce. Able to articulate the trade-offs involved - OLAP vs transactional systems, warehouses vs distributed compute, when to create different kinds of search indices.
• Experience building MCP servers and developing APIs with a focus on ease of LLM integration.
• Experience with graph databases - Neo4J preferred as this is commonly used by our customers, but experience with other databases is still valuable.
• Experience managing schema evolution in production - handling downstream breakages, contract changes, and backwards-compatible migrations.
• Hands-on experience building or maintaining dbt projects (or equivalent transformation tooling), including modelling, testing, documentation, and CI.
• Experience working with distributed compute systems such as Spark or Beam to process large-scale datasets in production.
• Experience running production orchestration systems such as Airflow, Dagster, or Prefect - authoring DAGs, handling failures, and managing dependencies.
• Experience with cloud data warehouses (Snowflake, BigQuery, Redshift)

Customer Facing Focus

• Ability to communicate effectively with both highly technical customer groups and internally
• High personal quality standards, bringing positive energy and able to thrive with ambiguity in a scale-up environment

Benefits

This is a rare opportunity to join Biorelate at an inflection point in our growth – and to genuinely shape how the company is seen and heard in the market. You'll work in a supportive team but you will have real autonomy to make this new role your own.

We offer competitive salaries, enhanced family leave, sick leave and significant opportunities for professional development. You’ll work alongside some of the brightest individuals, contributing to meaningful work that has a direct impact on global healthcare.

In addition, you can expect:

• Genuine Flexibility: We are a fully remote business with colleagues across the globe: manage your schedule, save time and money on commuting, and do your best work from the comfort of your home.
• Cutting-Edge Technology: You’ll work with the latest software tools and technologies; we’ll push you to genuinely be innovative and find new ways to solve the newest challenges.