At a Glance
- Tasks: Build innovative ML solutions and shape high-impact research platforms.
- Company: Dynamic tech firm in London, merging finance and cutting-edge technology.
- Benefits: Competitive pay, 35 days leave, free lunch, and a relaxed dress code.
- Other info: Inclusive culture with excellent career growth and monthly company events.
- Why this job: Join a team that values creativity and offers real impact in finance tech.
- Qualifications: Strong software engineering skills and a passion for ML workflows.
The predicted salary is between 60000 - 80000 £ per year.
We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. From our London HQ, we unite world‑class researchers and engineers in an environment that values deep exploration and methodical execution – because the best ideas take time to evolve. Together we’re building a world‑class platform to amplify our teams’ most powerful ideas. As part of our engineering team, you’ll shape the platforms and tools that drive high‑impact research – designing systems that scale, accelerate discovery and support innovation across the firm.
Responsibilities
- We are looking for exceptional engineers to help us build out a mature ML research and deploy pipeline as part of our ML Workflows team.
- You will develop green‑field solutions to meet highly complex ML interdependency requirements.
- Where off‑the‑shelf tools fall‑short, you’ll build custom solutions to define best practice across quantitative research.
Future Projects
- Implementing best practice feature and model stores
- Properly versioning features, data and models
- Improving inference compute utilisation via model serving
- CI/CD for ML
- Reliably fitting models with complex job dependency graphs
- Robustness in production, including validation and monitoring
Qualifications
- An appreciation of good architecture and MLOPs best practice
- The ability to collaborate with, and influence, technical and non‑technical people
- A passion for end‑to‑end ownership of solutions, from articulation to delivery
- Proven ability to engineer high‑quality software
- Effective decision‑making, with a focus on the mid to long term
- Value‑oriented and able to independently prioritise
- Finance experience is not necessary for this role and candidates from non‑financial backgrounds are encouraged to apply.
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
- Cycle‑to‑work scheme
- Monthly company events
Equal Opportunity Statement
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.
Company Culture
We are passionate about the intersection of finance, technology, and the future. We offer a dynamic, flexible and highly stimulating culture where world‑beating ideas are cultivated and rewarded. We are proud to employ some of the best people in their field and to nurture their talent in our collaborative working environment.
Machine Learning Workflow Engineer employer: Barlowe LLP
At G-Research, we pride ourselves on being an exceptional employer, offering a dynamic and inclusive work culture that fosters innovation and collaboration. Our London HQ provides a stimulating environment where talented engineers can thrive, with opportunities for professional growth, competitive compensation, and generous benefits including 35 days of annual leave and a comprehensive healthcare package. Join us to be part of a team that values deep exploration and empowers you to shape the future of quantitative finance through cutting-edge machine learning solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Workflow Engineer
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. We can’t stress enough how valuable personal connections can be when it comes to landing that dream job.
✨Show Off Your Skills
Don’t just talk about your experience; show it! Create a portfolio showcasing your projects, especially those related to machine learning workflows. We love seeing practical examples of your work, so make sure to highlight your best stuff!
✨Ace the Interview
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common interview questions and scenarios you might face. Remember, we’re looking for problem solvers, so think out loud during the interview to showcase your thought process.
✨Apply Through Our Website
We encourage you to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in joining our team. Don’t miss out on this opportunity!
We think you need these skills to ace Machine Learning Workflow Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Machine Learning Workflow Engineer role. Highlight any relevant projects or technologies you've worked with, especially those related to MLOps and software engineering.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about this role and how your background makes you a great fit. Be sure to mention your enthusiasm for building custom solutions and your appreciation for good architecture.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled complex problems in the past. We love seeing candidates who can think critically and come up with innovative solutions, especially in the context of ML workflows.
Apply Through Our Website:We encourage you to apply directly through our website. This way, we can ensure your application gets the attention it deserves, and you can easily keep track of your application status!
How to prepare for a job interview at Barlowe LLP
✨Understand the Role Inside Out
Before your interview, make sure you thoroughly understand the responsibilities of a Machine Learning Workflow Engineer. Familiarise yourself with concepts like MLOps best practices and CI/CD for ML. This will help you articulate how your skills align with their needs.
✨Showcase Your Problem-Solving Skills
Be prepared to discuss specific examples where you've tackled complex problems in your previous roles. Highlight any custom solutions you've built when off-the-shelf tools weren't enough. This demonstrates your ability to think critically and innovate.
✨Communicate Effectively with Diverse Teams
Since the role involves collaborating with both technical and non-technical people, practice explaining complex concepts in simple terms. This will show that you can bridge the gap between different teams and ensure everyone is on the same page.
✨Prepare Questions That Matter
At the end of the interview, you'll likely have the chance to ask questions. Prepare thoughtful queries about their ML research pipeline or future projects. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
