Staff AI Engineer

Staff AI Engineer

Edinburgh Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Design and deploy AI features to enhance healthcare for older adults.
  • Company: Join a remote-first HealthTech company making a real impact with AI.
  • Benefits: Enjoy full-time remote work and a collaborative, innovative environment.
  • Why this job: Be a founding member of the AI team, shaping the future of healthcare.
  • Qualifications: Minimum 5 years experience in AI, preferably in start-up or scale-up settings.
  • Other info: Work closely with a tight-knit team and receive regular feedback from care partners.

The predicted salary is between 43200 - 72000 £ per year.

We are looking for a founding Staff AI Engineer role with a remote-first HealthTech company building AI products that actually make a difference. Think: applied LLMs and symbolic AI to improve how care is delivered to older adults across millions of monthly visits. This is a high-priority, greenfield hire with strong backing, real product traction, and one of Europe’s largest structured healthcare datasets.

What makes this stand out:

  • Founding AI team member, reporting directly to the Head of AI
  • Hands-on from design to deployment, including infra and validation
  • Strong product exposure, weekly feedback loops with care partners
  • Stack includes SageMaker, Vertex, OpenAI APIs, PyTorch
  • Full-time, remote-first (UK/CET)

Your Responsibilities:

  • Designing and shipping AI-powered product features using LLMs and symbolic AI
  • Building out scalable infrastructure for model deployment and evaluation
  • Collaborating closely with engineers, PMs, and end users to iterate fast
  • Integrating models with the platform through well-designed APIs
  • Validating performance with real-world workflows and production data
  • Contributing to a lean, high-trust MVP team

Team so far:

You would be joining a tight-knit squad with a Principal PM and Full Stack Engineer, working closely with product, design, and end users. They want someone comfortable owning full-stack AI problems, deploying models into production, and iterating quickly in a product-led environment. Ideally, someone with a minimum of 5 years of experience would be suitable for this position (Start-up/Scale-up environments would be preferred).

If you feel you would be a good fit for this position, feel free to send your updated resume/CV!

Staff AI Engineer employer: DeepRec.ai

Join a pioneering HealthTech company as a founding Staff AI Engineer, where you'll have the unique opportunity to shape AI products that significantly enhance care for older adults. With a remote-first culture, strong backing, and access to one of Europe’s largest healthcare datasets, you will thrive in a collaborative environment that prioritises innovation and rapid iteration. Enjoy meaningful work, a supportive team dynamic, and the chance to grow your skills while making a real impact in the healthcare sector.
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Contact Detail:

DeepRec.ai Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff AI Engineer

✨Tip Number 1

Familiarise yourself with the specific technologies mentioned in the job description, such as SageMaker, Vertex, and PyTorch. Having hands-on experience or projects that showcase your skills with these tools will make you stand out.

✨Tip Number 2

Highlight any previous experience you have in a start-up or scale-up environment. This role is looking for someone who can thrive in fast-paced settings, so sharing relevant examples will demonstrate your adaptability.

✨Tip Number 3

Prepare to discuss how you've collaborated with cross-functional teams in the past. Since this position involves working closely with engineers, PMs, and end users, showcasing your teamwork skills will be crucial.

✨Tip Number 4

Think about real-world applications of AI in healthcare that excite you. Being able to articulate your vision for how AI can improve care delivery will resonate well with the hiring team and show your passion for the field.

We think you need these skills to ace Staff AI Engineer

Expertise in Large Language Models (LLMs)
Symbolic AI Knowledge
Experience with AI Product Development
Proficiency in PyTorch
Familiarity with SageMaker and Vertex
API Design and Integration Skills
Model Deployment and Evaluation Techniques
Strong Collaboration Skills
Understanding of Healthcare Data
Performance Validation with Real-World Workflows
Full-Stack Development Experience
Agile Methodologies
Problem-Solving Skills
Adaptability in Fast-Paced Environments

Some tips for your application 🫡

Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Staff AI Engineer position. Familiarise yourself with the technologies mentioned, such as LLMs, symbolic AI, and the specific tools like SageMaker and PyTorch.

Tailor Your CV: Customise your CV to highlight relevant experience in AI, particularly in deploying models and working in start-up or scale-up environments. Emphasise any hands-on experience with the technologies listed in the job description.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for HealthTech and how your skills align with the company's mission. Mention specific projects where you've successfully implemented AI solutions and how they made a difference.

Highlight Collaboration Skills: Since the role involves close collaboration with engineers, PMs, and end users, be sure to include examples of how you've effectively worked in teams. This could include experiences where you iterated on products based on user feedback.

How to prepare for a job interview at DeepRec.ai

✨Showcase Your Technical Skills

Be prepared to discuss your experience with LLMs, symbolic AI, and the tech stack mentioned in the job description. Highlight specific projects where you've designed and deployed AI models, especially in a healthcare context.

✨Demonstrate Collaboration Experience

Since the role involves working closely with engineers, PMs, and end users, share examples of how you've successfully collaborated in cross-functional teams. Emphasise your ability to iterate quickly based on feedback.

✨Understand the Product and Its Impact

Research the company’s products and their impact on older adults' care. Be ready to discuss how you can contribute to improving these services through AI, showing that you’re aligned with their mission.

✨Prepare for Problem-Solving Scenarios

Expect technical questions or case studies that assess your problem-solving skills. Practice articulating your thought process when tackling full-stack AI challenges, particularly in a production environment.

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