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For Companies At a Glance
- Tasks: Build and ship AI features that make technology work for users in real-world scenarios.
- Company: Join a forward-thinking AI company focused on proactive systems and user experience.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and continuous improvement.
- Why this job: Be at the forefront of AI innovation and make a tangible impact on everyday technology.
- Qualifications: Experience in machine learning, coding skills, and a passion for problem-solving.
The predicted salary is between 60000 - 80000 ÂŁ per year.
A1 is building a proactive AI system that understands context across conversations, plans actions, and carries work forward over time. As an Applied AI Engineer, you will turn model capabilities into real product behavior. You will own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production. This role sits at the intersection of machine learning, systems, and product, focusing on making AI actually work for users, not just in demos, but in real‑world usage.
Responsibilities
- Build and ship AI features end-to-end (model system user experience)
- Design and iterate on prompts, tools, memory, and agent workflows
- Turn raw model outputs into structured, reliable, and predictable behaviors
- Debug issues across the full stack (model, orchestration, infra, UX)
- Optimize for latency, cost, and production reliability
- Develop lightweight evaluation frameworks to measure real‑world performance
- Work closely with product and engineering to translate ambiguous problems into working systems
Tech Stack
- Python
- PyTorch/JAX
- LLMs (OpenAI‑style APIs, LLaMA, Qwen, etc.)
- Inference/serving (e.g., vLLM)
- Vector DB
Ideal Experience
- Strong foundation in machine learning and modern neural network architectures
- Hands‑on experience with training, fine‑tuning, or deploying ML models
- Ability to write clean, production‑quality code
- Comfort working across abstraction layers (model, infra, product)
- Strong problem‑solving skills in ambiguous, fast‑moving environments
- Bias toward shipping, iteration, and continuous improvement
Outcomes
- ML models in production meet expected accuracy, latency, and reliability targets
- Production issues are identified quickly, debugged effectively, and root causes addressed
- Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable
- Collaboration with engineers, product, and research teams delivers reliable ML‑powered features
- Iterations on models and systems are driven by real‑world signals and measurable improvements
Applied AI Engineer in London employer: Bjak Sdn Bhd
Contact Detail:
Bjak Sdn Bhd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and machine learning space, especially those who work at companies you're interested in. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, PyTorch, or any LLMs. Real-world examples of your work can make you stand out in interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your problem-solving skills. Practice coding challenges and be ready to discuss how you've tackled ambiguous problems in the past.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Plus, it gives you a better chance to showcase your enthusiasm for the role.
We think you need these skills to ace Applied AI Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Applied AI Engineer role. Highlight your experience with machine learning, Python, and any relevant projects that showcase your ability to turn model capabilities into real product behaviour.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled ambiguous problems in fast-moving environments. We love seeing candidates who can demonstrate their strong problem-solving skills and a bias towards shipping and continuous improvement.
Highlight Collaboration Experience: Since this role involves working closely with product and engineering teams, make sure to mention any past experiences where you collaborated effectively. We want to see how you can translate ambiguous problems into working systems alongside others.
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 ensure 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 Bjak Sdn Bhd
✨Know Your Tech Stack
Familiarise yourself with the specific technologies mentioned in the job description, like Python, PyTorch, and LLMs. Be ready to discuss your hands-on experience with these tools and how you've used them to build or optimise AI features in the past.
✨Showcase Problem-Solving Skills
Prepare examples that highlight your ability to tackle ambiguous problems. Think of situations where you had to debug issues across different layers, from model to user experience, and be ready to explain your thought process and the outcomes.
✨Demonstrate Your Shipping Mindset
This role values a bias towards shipping and iteration. Share instances where you’ve successfully delivered projects on time, focusing on how you iterated based on feedback and real-world performance metrics.
✨Engage with Real-World Applications
Be prepared to discuss how you can turn model capabilities into practical applications. Think about how you would approach designing prompts and workflows that enhance user experience, and be ready to share your ideas during the interview.