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- Tasks: Design and implement AI systems to transform complex scientific data into clear documents.
- Company: TriloDocs, a tech company revolutionising life sciences with innovative AI solutions.
- Benefits: Flexible remote work, collaborative culture, and the chance to shape the future of GenAI.
- Why this job: Make a real impact in healthcare by developing cutting-edge AI technologies.
- Qualifications: 3-6 years in AI/ML, strong Python skills, and experience with LLMs.
- Other info: Join a dynamic startup environment with global reach and flat hierarchies.
The predicted salary is between 36000 - 60000 £ per year.
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.
AI Engineer in Telford employer: TriloDocs (part of Genactis Group)
Contact Detail:
TriloDocs (part of Genactis Group) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer in Telford
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Generative AI and LLMs. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common AI and NLP questions. Practice explaining your past projects and how they relate to the role at TriloDocs. Confidence is key, so get comfortable talking about your experience!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at TriloDocs.
We think you need these skills to ace AI Engineer in Telford
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and its potential in life sciences shine through. We want to see how your experience aligns with our mission to transform scientific data into clear documents.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your experience with Generative AI, LLMs, and any relevant projects that demonstrate your skills. We love seeing how you can contribute to our team!
Be Clear and Concise: In your written application, clarity is key. Use straightforward language to explain your technical skills and experiences. We appreciate well-structured applications that make it easy for us to understand your qualifications.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at TriloDocs (part of Genactis Group)
✨Know Your Generative AI Inside Out
Make sure you brush up on your knowledge of Generative AI and Large Language Models. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show that you not only understand the theory but also have practical experience.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex datasets in the past. Think of examples where you designed or fine-tuned models for document understanding or summarisation. Highlight your analytical skills and how they contributed to successful outcomes.
✨Familiarise Yourself with Relevant Tools
Get comfortable with the tools mentioned in the job description, like Python, LLM APIs, and MLOps practices. If you’ve used Docker or FastAPI, be ready to share your experiences. This will demonstrate your technical proficiency and readiness to hit the ground running.
✨Communicate Clearly and Confidently
Since the role involves collaboration with developers and domain experts, practice explaining complex concepts in a clear and concise manner. Use examples from your past work to illustrate your points, ensuring you convey reliability and clarity in your communication.