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- Tasks: Lead the development of cutting-edge machine learning models and systems.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on high-impact projects and user experience.
- Why this job: Make a real impact by shaping the future of machine learning technology.
- Qualifications: Experience in building real ML systems and strong coding skills required.
The predicted salary is between 80000 - 100000 £ per year.
Responsibilities
- Adapt models using state‑of‑the‑art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
- Architect and operate scalable inference systems, balancing latency, cost, and reliability.
- Design and maintain data systems for high‑quality synthetic and real‑world training data.
- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
- Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.
- Make pragmatic trade‑offs and ship improvements quickly, learning from real usage.
- Work under real production constraints: latency, cost, reliability, and safety.
- Ensure ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.
- Detect, debug, and resolve production issues quickly, minimizing user impact.
- Support team members, align them, and foster delivery of high‑impact ML work with minimal friction.
- Iterate on models and systems that are measurable, safe, and improve user experience over time.
Qualifications
- You have built or shipped real ML systems used by people, not just demos.
- You are comfortable working with large models and understanding their failure modes.
- You write strong, production‑grade code and care about system correctness.
- You are self‑directed, pragmatic, and take full ownership of outcomes.
- You communicate clearly and collaborate well in small, high‑trust teams.
Technical Stack
- Python, PyTorch / JAX, GPU‑based training and inference system.
Technical Lead, Machine Learning in City of Westminster employer: Bjak Sdn Bhd
Contact Detail:
Bjak Sdn Bhd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Technical Lead, Machine Learning in City of Westminster
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that demonstrate your ability to adapt models and handle real-world data. This will give you an edge and make you stand out during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding the latest ML methods like LoRA and QLoRA. Practice solving problems under time constraints to simulate real interview conditions.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight how your experience aligns with our mission and the role.
We think you need these skills to ace Technical Lead, Machine Learning in City of Westminster
Some tips for your application 🫡
Show Off Your Skills: When you're writing your application, make sure to highlight your experience with ML systems. We want to see how you've adapted models and tackled real-world challenges, so don’t hold back on the details!
Be Clear and Concise: We love a good story, but keep it relevant! Use clear language to describe your past projects and how they relate to the role. This helps us understand your thought process and how you approach problem-solving.
Tailor Your Application: Make sure to align your application with our job description. Mention specific methods like LoRA or QLoRA that you’ve worked with, and show us how you balance latency, cost, and reliability in your projects.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at Bjak Sdn Bhd
✨Know Your Models Inside Out
Make sure you’re well-versed in the state-of-the-art methods mentioned in the job description, like LoRA and QLoRA. Be ready to discuss how you've adapted models in the past and the impact of those adaptations on performance and user experience.
✨Showcase Your Production Experience
Prepare examples of real ML systems you've built or shipped. Highlight your experience with production constraints such as latency and cost, and be ready to discuss how you’ve tackled issues like debugging and system stability.
✨Communicate Your Collaboration Skills
Since collaboration is key, think of specific instances where you’ve worked closely with application engineering teams. Share how you ensured smooth integration of ML systems into products and how you supported team members to achieve high-impact results.
✨Demonstrate Pragmatic Decision-Making
Be prepared to discuss how you make trade-offs when shipping improvements. Use examples to illustrate your ability to balance speed and quality while learning from real usage, showing that you can adapt quickly under pressure.