AI Engineer
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
+5 more
Job description
· Design and implement ML/AI solutions end-to-end, from the idea and data exploration phase to deployment and monitoring, balancing cutting-edge techniques with pragmatism to deliver measurable impact.
· Apply strong software engineering principles, such as modularity, testing, code reviews, CI/CD and observability, to ensure AI systems are reliable, maintainable, production-ready and can be readily adapted to future developments.
· Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM-based solutions, and agentic solutions to balance trade-offs between speed, cost, complexity, interpretability, and performance.
· Collaborate closely with product, design, and other engineering teams to scope work, align on success metrics, and incrementally ship improvements in user-facing features powered by AI.
· Document system architectures and decision rationale early and clearly, enabling alignment across teams and accelerating onboarding and iteration.
· Champion model and data quality, including dataset versioning, robust evaluation, fairness/bias assessment, and real-world performance tracking.
· Mentor junior AI engineers and cross-functional teammates, sharing best practices in modelling, coding, maintaining and integrating product features, and helping grow a high-trust, high-performance team culture.
· Stay up-to-date with emerging research and tools, distilling key insights and bringing back relevant innovations to elevate team capabilities and product opportunities.
· Contribute to a culture of knowledge sharing, through company-wide Slack channels, Show and Tell presentations and technical deep-dives.
Requirements
· A master’s degree or above in Computer Science, Electrical Engineering or a related field.
· 5+ years of experience building AI/ML systems in production environments, including ownership of key lifecycle stages: data collection, modeling, evaluation, deployment, and monitoring.
· Proficiency in Python and modern ML and agentic frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications.
· A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt engineering and fine-tuning.
· Strong software engineering foundations such as version control, unit/integration testing, CI/CD, containerization plus a mindset of building for reliability and scale.
· Experience working in product-focused teams, collaborating with designers, engineers, and PMs, to scope and ship AI features iteratively
· Ability to reason about system behavior end-to-end, including model performance, latency, and observability, and how these impact user experience.
· Clear, structured communicator, comfortable documenting and defending architectural decisions and engaging in thoughtful technical debate.
Not required, but it’s a plus if you also have:
· Experience with MLOps/LLMOps frameworks and best practices
· A PhD in Computer Science, Electrical Engineering or a related field.
· A background or work experience in life-sciences, health-tech, or other data-intensive domains
Benefits & conditions
Competitive compensation package
Private medical & dental insurance
Life insurance (4 x salary)
Personal development budget
Individual wellbeing budget
25 days holiday plus bank holidays
Your birthday off!
Potential to have real impact and accelerated career growth as a member of an international team that’s building a transformative AI product.
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
What Are Large Language Models?
MLOps And AI Driven Development
MLOps – What’s the deal behind it?
What Industries Outside of AI Are Hiring The Most AI Experts?