Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead a team to develop scalable ML solutions and define long-term strategies.
- Company: Top quantitative research firm in Greater London with a focus on innovation.
- Benefits: Competitive pay, flexible work options, and extensive benefits package.
- Why this job: Shape the future of machine learning while mentoring a talented team.
- Qualifications: Strong ML infrastructure background and excellent communication skills.
- Other info: Dynamic role with opportunities for professional growth and impact.
The predicted salary is between 48000 - 72000 £ per year.
A leading quantitative research firm in Greater London seeks an Engineering Manager to lead its ML Workflows team. You will be responsible for defining the long-term strategy for machine learning research, guiding a team of engineers to develop scalable and efficient solutions.
The ideal candidate will possess a strong engineering background in ML infrastructure, effective communication skills, and a proven track record in mentoring engineers.
This position offers competitive compensation, flexible work environment, and substantial benefits.
ML Operations Lead - Scalable Pipelines & Platform employer: G-Research
Contact Detail:
G-Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Operations Lead - Scalable Pipelines & Platform
✨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 projects and achievements in ML infrastructure. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and problem-solving scenarios. Practice explaining your thought process clearly, as communication is key in this 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 are proactive about their job search.
We think you need these skills to ace ML Operations Lead - Scalable Pipelines & Platform
Some tips for your application 🫡
Show Off Your Engineering Skills: When you're writing your application, make sure to highlight your engineering background in ML infrastructure. We want to see how your experience aligns with the role, so don’t hold back on those technical details!
Communicate Clearly: Effective communication is key for us at StudySmarter. Use your application to demonstrate how you can convey complex ideas simply and clearly. This will show us that you can lead a team effectively.
Mentorship Matters: If you've got experience mentoring engineers, let us know! Share specific examples of how you've guided others in their careers. This will help us see your leadership style and how you can contribute to our team.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at G-Research
✨Know Your ML Infrastructure
Make sure you brush up on your knowledge of machine learning infrastructure. Be prepared to discuss specific technologies and frameworks you've worked with, as well as how they can be applied to scalable pipelines. This will show that you have the technical chops for the role.
✨Showcase Your Leadership Skills
Since this role involves leading a team, think about examples from your past where you've successfully mentored engineers or led projects. Prepare to share these stories during the interview to demonstrate your leadership style and how you can guide a team effectively.
✨Communicate Clearly
Effective communication is key in this position. Practice explaining complex ML concepts in simple terms, as you may need to convey ideas to non-technical stakeholders. This will highlight your ability to bridge the gap between technical and non-technical teams.
✨Align with Their Vision
Research the company's long-term strategy for machine learning research. Be ready to discuss how your vision aligns with theirs and how you can contribute to their goals. This shows that you're not just looking for a job, but are genuinely interested in being part of their mission.
