At a Glance
- Tasks: Lead quality assurance efforts and enhance ML product initiatives with your expertise.
- Company: Join Hudl, a forward-thinking company in the tech space.
- Benefits: Enjoy a competitive salary and a supportive remote work culture.
- Other info: Be part of a dynamic team with opportunities for growth and innovation.
- Why this job: Make a real impact on machine learning products while mentoring fellow engineers.
- Qualifications: Strong background in quality assurance and MLOps with excellent collaboration skills.
The predicted salary is between 60000 - 80000 £ per year.
Hudl is looking for a Lead Quality Assurance Engineer to join its Applied Machine Learning team. This role involves providing technical leadership, owning the architecture for quality infrastructure, and collaborating across departments to enhance ML product initiatives.
You will be a key contributor, design measuring systems, and mentor other engineers, ensuring high standards of quality and effectiveness in deliveries.
The successful candidate should have a strong background in quality assurance, MLOps, and excellent remote collaboration skills. This position offers a competitive salary range and a supportive work culture.
Lead QA Engineer - ML Platform & MLOps (Remote UK) in London employer: Hudl
Hudl is an exceptional employer that fosters a collaborative and innovative work culture, particularly for remote roles like the Lead QA Engineer. With a strong emphasis on employee growth and mentorship, Hudl provides opportunities to lead impactful projects in the rapidly evolving field of machine learning, all while enjoying a competitive salary and a supportive environment that values quality and effectiveness.
StudySmarter Expert Advice🤫
We think this is how you could land Lead QA Engineer - ML Platform & MLOps (Remote UK) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Hudl or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your QA projects, especially those related to ML and MLOps. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common QA scenarios and MLOps challenges. Practice articulating your thought process and problem-solving skills, as this is key for a Lead role.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Lead QA Engineer - ML Platform & MLOps (Remote UK) in London
Some tips for your application 🫡
Show Off Your Experience:When you're writing your application, make sure to highlight your background in quality assurance and MLOps. We want to see how your past experiences align with the role, so don’t hold back on those relevant projects!
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Remember, we’re looking for effective communication skills, especially since this is a remote position.
Tailor Your Application:Make sure to customise your application for the Lead QA Engineer role. Mention specific aspects of the job description that excite you and how you can contribute to our Applied Machine Learning team. It shows us you’ve done your homework!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Hudl
✨Know Your Stuff
Make sure you brush up on your quality assurance principles, MLOps practices, and any relevant machine learning concepts. Be ready to discuss how you've applied these in past roles, as this will show your technical expertise and leadership potential.
✨Showcase Your Collaboration Skills
Since this role involves working across departments, prepare examples of how you've successfully collaborated with different teams in the past. Highlight any specific projects where your communication and teamwork made a significant impact.
✨Prepare for Technical Questions
Expect some technical questions that assess your problem-solving skills and understanding of quality infrastructure. Practise articulating your thought process clearly, as this will demonstrate your ability to lead and mentor others effectively.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current ML product initiatives or how they measure success in quality assurance. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
