Senior AI/ML Engineer | NDA

GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.

On behalf of our client, GT is looking for Senior AI/ML Engineer to join an ambitious project in the life sciences domain.
Experience in the life sciences domain is a must for this role.

About the Client & the Project

We are an AI company building foundational infrastructure for life sciences regulatory operations. Our platform reimagines how regulatory teams generate, validate, and deliver compliant documentation at scale. We’re blending cutting-edge LLMs, intelligent workflows, and human-centered design to accelerate drug time to market.

As our first engineering hire, you’ll shape the core technology behind a product poised to redefine one of the most overlooked bottlenecks in healthcare innovation. This is a unique opportunity to join at the inception and help launch something with enduring impact.

Working hours: It is essential to have at least 3 working hours of overlap with West Coast time.

Responsibilities:

• Architect & build agentic AI workflows

  • Develop end-to-end pipelines for Regulatory document generation, Quality Control analyses, and e-publishing.

  • Design GraphRAG architectures combining knowledge graphs with retrieval-augmented generation (GraphRAG is a must-have; ability to build from scratch strongly preferred).

  • Perform prompt engineering, fine-tuning (HuggingFace, OpenAI API), and model lifecycle management (MLOps/CI-CD).

  • Build AI systems to interpret Tabular, Figure, and Listing (TFL) data from medical & technical reports, returning accurate textual insights, and to construct, manipulate, and validate table drafts from unstructured text.

  • Develop AI-powered systems to validate regulatory documents against FDA formatting, content, and structure guidelines (e.g., eCTD, Module 1-5).

  • Encode and apply domain-specific rules (e.g., reference integrity, missing study summaries, sequence validation) to flag errors before submission, reducing risk of rejection or delay.

• Design secure, compliant systems

  • Enforce data governance, audit logging, and 21 CFR Part 11 controls.

  • Partner on system validation and information-security processes tailored to regulated environments.

• Build advanced document search systems

  • Architect scalable full-text and vector-based search across hundreds to thousands of pages and multiple document types.

  • Optimize indexing, relevance ranking, and federated search for cross-document and multi-file queries.

• Embed human-in-the-loop

  • Craft interfaces for regulatory experts to review, correct, and guide AI outputs.

  • AI UX/UI expertise to design intuitive, workflow-augmented interfaces that streamline human review and decision-making.

  • Instrument continuous feedback loops to enhance model accuracy, trust, and compliance.

Essential knowledge, skills & experience:

• Deep AI/ML expertise

  • 5+ years in ML/AI engineering; 2+ years architecting production LLM and agentic AI applications.

  • Ability to build and apply graph-based knowledge representations in model inference (GraphRAG).

  • Experience with fine-tuning transformer-based models (e.g., HuggingFace, Fireworks, or equivalent).

  • Understanding of LLM evaluation frameworks (e.g., HELM, TruthfulQA, or other equivalent internal tools).

  • Built human-in-the-loop feedback loops for continuous learning and accuracy validation.

• Enterprise software expertise

  • Proven experience building and deploying enterprise-grade software in life sciences (2+ years).

  • Familiarity with compliance standards (21 CFR Part 11, GxP, ISO) and secure system design.

  • Deep understanding of enterprise-specific needs: access control, auditability, user roles, performance at scale, and integration with internal systems.

  • Experience collaborating with enterprise IT and compliance stakeholders.

  • Familiarity integrating with SharePoint, Box, and other industry specific repositories like Veeva Vault & MasterControl.

• MLOps & Infrastructure (Preferred)

  • Designed scalable AI microservices (FastAPI, gRPC, etc.) deployed via Docker/K8s in cloud environments.

• Startup Experience (Preferred)

  • 2+ year in early stage startup engineering

  • Demonstrated ability to learn complex domains quickly and deliver under tight timelines.

  • Self-starter who thrives with ambiguity, rapid iteration, and evolving priorities.

• UX/UI excellence

  • Proven ability to translate complex backend logic into intuitive, responsive UI/UX experiences for regulated environments.

  • Experience designing collaborative interfaces where users and AI can jointly create, review, and refine documents within a unified environment

Soft Skills

• Outstanding communication & collaboration

  • Translate technical concepts into clear, simple language for stakeholders with limited technical backgrounds.

  • Excellent written/verbal skills; adept at writing API docs, design specs, and user guides.

• Take initiative. If you see opportunities to own tasks or improve processes, speak up and step in. Don’t wait to be asked. 

• Communicate proactively. Raise potential issues early when they’re small and always close the loop on open items. If you are in doubt, overcommunicate.

• Be tenacious. Ask clarifying questions until you fully understand. Own challenging projects end-to-end and become the go to person who delivers results, no matter the difficulty.

• Open-source champion. Stay at the forefront of AI developments, engage with open-source communities, and leverage open-source frameworks wherever possible.

• Be pragmatic. Ship V1 fast but understand what enterprise-grade means when it’s time to harden.

• Be constructive. Do not just say yes – challenge assumptions, raise risks, and improve ideas.

Interview Steps

1. GT Interview

2. Cultural Fit Interview

3. Technical Interview

4. Offer

We go beyond usual perks… By working with us, you will get:

• Health insurance.

• Psychotherapy coverage.

• Sport coverage.

• Learning budget.

• Paid vacations

• Paid sick leaves.

• All public holidays are paid days off.

GT working model:

You will work directly with a client through our Extended Team model. We try to do things differently and put our efforts into integrating you as deeply as possible into the client’s team. You work with the same tools and technologies as they do and are managed directly by the client without any intermediary in between. We help you build relationships and create an environment where you genuinely feel like a member of the client’s team. We also encourage trips to a client and join teambuilding and after-work activities. Our Extended Team model is focused on long-term projects that last over several years.