AI Engineer

About TriloDocs

TriloDocs is a growing company at the intersection of technology and life sciences. We help pharma and healthcare organizations transform scientific data into clear, structured documents. Our team is passionate about creating intuitive, reliable tools that make a real difference in how scientific information is communicated and understood.

The Role

We’re looking for a Mid-Level to Senior AI Engineer with strong experience in Generative AI and Large Language Models (LLMs) . You’ll help design and implement intelligent systems that use GenAI to automate, summarize, and generate scientific and clinical content — turning complex datasets into clear, human-readable outputs.

This role combines technical depth with creativity: you’ll prototype, fine-tune, and deploy generative models, and collaborate with developers, and domain experts to deliver AI capabilities that are both powerful and trustworthy.

Responsibilities

• Design, train, and deploy Generative AI and NLP models for document understanding, summarization, and generation.
• Work with LLM APIs (e.g., OpenAI, Anthropic, Mistral) and open-source models (e.g., Llama, Falcon, Mixtral) for custom workflows.
• Build scalable pipelines and services that integrate GenAI into production systems.
• Fine-tune and evaluate models to balance performance, factual accuracy, and explainability.
• Develop prompt engineering strategies pipelines using domain-specific data.
• Contribute to architecture decisions around model deployment, data security, and performance optimization.
• Collaborate cross-functionally to translate scientific and business requirements into AI-powered solutions.

Qualifications

• 3–6 years of experience developing and deploying AI/ML or NLP systems, including Generative AI applications .
• Bachelor’s or Master’s degree in a STEM field (Computer Science, Data Science, Engineering, Mathematics, etc.).
• Strong proficiency in Python
• Hands-on experience with LLMs , prompt design , RAG architectures , or fine-tuning foundation models .
• Understanding of MLOps practices (e.g., Docker, FastAPI, MLflow, cloud-based model deployment).
• Strong grasp of NLP techniques and evaluation methods for generative models.
• Excellent analytical and communication skills, with a focus on clarity and reliability in AI outputs.
• Experience with scientific, healthcare, or regulated data is a plus.

What We Offer

• A chance to shape the future of GenAI in life sciences.
• Flexible, remote-first work environment.
• A collaborative, startup culture with global reach — based in London but working across borders.
• Flat hierarchies and direct communication.
• Meaningful work at the intersection of AI, science, and human health .