AI Engineer
5 days ago
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
.
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