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- Tasks: Lead ML workflow engineers and shape the future of ML research.
- Company: Top quantitative research firm in London with a focus on innovation.
- Benefits: Competitive pay, flexible benefits, and great work-life balance.
- Why this job: Make a real impact in ML while leading a talented team.
- Qualifications: Strong ML infrastructure or MLOps background with leadership experience.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 43200 - 72000 £ per year.
A leading quantitative research firm in London is seeking a technical leader to oversee machine learning (ML) workflow engineers and shape the long-term strategy for ML research. Ideally, candidates will have strong backgrounds in ML infrastructure or MLOps, with proven leadership experience. The role includes hands-on leadership, collaboration with various teams, and a focus on delivering high-quality ML systems. The firm offers competitive compensation, flexible benefits, and an excellent work-life balance.
ML Workflow Leader: Production ML & MLOps in London employer: G-Research
Contact Detail:
G-Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Workflow Leader: Production ML & MLOps in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with ML professionals 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 and MLOps experience. This is your chance to demonstrate your hands-on leadership and technical prowess, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Be ready to discuss your leadership style and how you collaborate with teams to deliver high-quality ML systems. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team!
We think you need these skills to ace ML Workflow Leader: Production ML & MLOps in London
Some tips for your application 🫡
Show Your Technical Skills: Make sure to highlight your experience with ML infrastructure and MLOps in your application. We want to see how your technical background aligns with the role, so don’t hold back on showcasing your expertise!
Demonstrate Leadership Experience: Since this role involves overseeing a team, it’s crucial to illustrate your leadership skills. Share examples of how you've led teams or projects in the past, and how you’ve driven success through collaboration.
Tailor Your Application: Take the time to customise your CV and cover letter for this specific role. We love seeing candidates who take the initiative to align their experiences with our needs, so make it clear why you’re the perfect fit for us!
Apply Through Our Website: We encourage you to submit your application directly 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!
How to prepare for a job interview at G-Research
✨Know Your ML Inside Out
Make sure you brush up on your machine learning concepts and MLOps practices. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show your technical depth and hands-on experience.
✨Showcase Your Leadership Skills
Prepare examples that highlight your leadership experience. Think about times when you led a team through a complex project or mentored junior engineers. This is crucial for demonstrating that you can oversee ML workflow engineers effectively.
✨Collaborate and Communicate
Since the role involves collaboration with various teams, practice articulating how you work with others. Be ready to discuss how you handle cross-functional communication and ensure everyone is aligned on project goals.
✨Align with Their Vision
Research the firm’s long-term strategy for ML research and be prepared to discuss how your vision aligns with theirs. Showing that you understand their goals and can contribute to them will set you apart from other candidates.
