Machine Learning Workflow Manager in London
Machine Learning Workflow Manager

Machine Learning Workflow Manager in London

London Full-Time 43200 - 72000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead a team to design and deliver ML workflows for cutting-edge research.
  • Company: G-Research, a leading tech firm in finance with a dynamic culture.
  • Benefits: Highly competitive salary, 35 days leave, healthcare, and monthly events.
  • Why this job: Shape the future of ML in finance and work with top talent.
  • Qualifications: Strong engineering background in ML infrastructure or MLOps required.
  • Other info: Inclusive environment with excellent work/life balance and growth opportunities.

The predicted salary is between 43200 - 72000 ÂŁ per year.

Do you want to tackle the biggest questions in finance with near infinite compute power at your fingertips? Do you want to be part of building and extending a world-class trading platform to amplify our teams' most powerful ideas? G-Research is a leading quantitative research and technology firm. We are proud to employ some of the best people in their field and to nurture their talent in a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded.

As part of our engineering team, you'll shape the platforms and tools that drive high-impact research and its deployment to production - designing systems that scale, accelerate discovery and support innovation across the firm. This role is based in our headquarters and home to our Research Lab, the new Soho Place office opened in 2023 in the heart of Central London.

We're looking for a technically strong Engineering Manager to lead our ML Workflows team. The team builds and operates the pipelines, tools and infrastructure that underpin our machine learning research and deployment ecosystem. You'll guide a team of skilled engineers to deliver scalable, reliable and efficient solutions that enable cutting-edge ML research. Where existing tools don't fit, you'll help define and build custom systems that set best practice across the organisation.

What you'll do:

  • Design and deliver the long-term strategy for how ML research happens at G-Research
  • Lead and develop a team of ML workflow engineers, fostering technical excellence and continuous improvement
  • Provide hands‐on technical leadership across design, architecture and implementation
  • Partner with research, data and infrastructure teams to deliver high‐impact workflow and MLOps solutions
  • Set direction for the evolution of ML pipelines, from experimentation through to production
  • Drive quality, reliability and observability across all stages of the ML lifecycle

Future projects:

  • Implementing best-practice feature and model stores
  • Versioning features, data and models
  • Improving inference compute utilisation through model serving
  • CI/CD for ML
  • Reliable model fitting with complex dependency graphs
  • Robust validation and monitoring in production

Who are we looking for?

We need a pragmatic technical leader who enjoys solving complex problems, enabling others, and delivering high-quality systems. You'll need:

  • Strong engineering background with experience in ML infrastructure or MLOps
  • Proven track record leading or mentoring engineers
  • Solid understanding of good architecture, CI/CD and production ML systems
  • Clear, effective communication across technical and non‐technical audiences
  • The ability to make sound decisions and prioritise for long‐term impact

Finance experience is not essential; we welcome candidates from all technical backgrounds.

Benefits:

  • Highly competitive compensation plus annual discretionary bonus
  • Lunch provided (via Just Eat for Business) and dedicated barista bar
  • 35 days' annual leave
  • 9% company pension contributions
  • Informal dress code and excellent work/life balance
  • Comprehensive healthcare and life assurance
  • Monthly company events

G-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas‐driven business and we place great value on diversity of experience and opinions. We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section.

Machine Learning Workflow Manager in London employer: G-Research

G-Research is an exceptional employer, offering a dynamic and flexible work culture that fosters innovation and technical excellence. Located in the heart of Central London, our new Soho Place office provides a stimulating environment where employees can thrive, with generous benefits including 35 days of annual leave, comprehensive healthcare, and opportunities for professional growth. Join us to be part of a world-class team dedicated to tackling complex challenges in finance using cutting-edge machine learning technologies.
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Contact Detail:

G-Research Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Workflow Manager in London

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at G-Research. A friendly chat can sometimes lead to opportunities that aren’t even advertised.

✨Tip Number 2

Show off your skills! If you’ve got a portfolio or any projects related to ML workflows, make sure to highlight them during interviews. We love seeing practical examples of your work and how you tackle complex problems.

✨Tip Number 3

Prepare for technical challenges! Brush up on your ML infrastructure knowledge and be ready to discuss your approach to building scalable systems. We want to see how you think and solve problems in real-time.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at G-Research.

We think you need these skills to ace Machine Learning Workflow Manager in London

Machine Learning Infrastructure
MLOps
Technical Leadership
Team Development
System Design
Architecture
CI/CD
Production ML Systems
Communication Skills
Problem-Solving Skills
Workflow Management
Scalability
Reliability
Observability

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Machine Learning Workflow Manager role. Highlight your engineering background, leadership experience, and any relevant projects you've worked on in ML infrastructure or MLOps.

Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about this role and how you can contribute to our team. Share specific examples of how you've solved complex problems or led teams in the past, and don’t forget to mention your enthusiasm for working in a dynamic environment like ours.

Showcase Your Technical Skills: In your application, be sure to highlight your technical expertise, especially in areas like CI/CD, production ML systems, and architecture. We want to see how you can bring your hands-on experience to the table and lead our ML workflows team effectively.

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 gives you a chance to explore more about our company culture and values!

How to prepare for a job interview at G-Research

✨Know Your ML Workflows

Before the interview, brush up on your knowledge of machine learning workflows and MLOps. Be ready to discuss specific tools and techniques you've used in the past, as well as how you would approach building scalable systems for ML research.

✨Showcase Your Leadership Skills

As a potential Engineering Manager, it's crucial to demonstrate your leadership abilities. Prepare examples of how you've mentored engineers or led teams in previous roles. Highlight your approach to fostering technical excellence and continuous improvement within a team.

✨Communicate Clearly

Effective communication is key, especially when discussing complex technical concepts. Practice explaining your past projects and decisions in a way that’s accessible to both technical and non-technical audiences. This will show that you can bridge the gap between different teams.

✨Prepare for Problem-Solving Questions

Expect to face questions that assess your problem-solving skills. Think about challenges you've encountered in ML infrastructure or CI/CD processes and how you overcame them. Be ready to walk through your thought process and decision-making strategies.

Machine Learning Workflow Manager in London
G-Research
Location: London

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