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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.
- Why this job: Make a real impact by shaping the future of machine learning technology.
- Qualifications: Experience in building 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 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
✨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 ML projects, especially those that demonstrate your ability to build real systems. This will give potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding the latest ML methods. Practice common interview questions and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight how your experience aligns with our needs.
We think you need these skills to ace Technical Lead, Machine Learning
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ML systems and the specific technologies mentioned in the job description. We want to see how you've tackled real-world challenges, so don’t hold back on those details!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your skills align with our needs. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Projects: If you've worked on any relevant projects, whether personal or professional, make sure to include them. We’re interested in your hands-on experience, especially with scalable inference systems and model optimisation.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen to join the StudySmarter team!
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 applied these techniques in real-world scenarios, as this will show your practical experience and understanding.
✨Demonstrate Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled production issues in the past. Highlight your ability to debug and resolve problems quickly while minimising user impact, as this is crucial for the role.
✨Showcase Your Collaboration Skills
Since the role involves working closely with application engineering, be prepared to discuss how you’ve successfully collaborated in small teams. Share examples that demonstrate your clear communication and ability to align team members towards common goals.
✨Be Ready to Discuss Trade-offs
Understand the balance between latency, cost, and reliability in ML systems. Be prepared to talk about pragmatic trade-offs you've made in previous projects and how those decisions impacted the overall success of the system.