At a Glance
- Tasks: Lead the evolution of a personalised recommendation system for an interactive learning tool.
- Company: Join Grafana Labs, a remote-first company with a collaborative culture and open-source values.
- Benefits: Enjoy competitive salary, RSUs, 30 days annual leave, and a supportive work environment.
- Other info: Work remotely with a global team and enjoy excellent career growth opportunities.
- Why this job: Make a real impact by developing innovative ML solutions in a fast-paced, growth-driven company.
- Qualifications: Experience in recommendation systems and applied model ownership is essential.
The predicted salary is between 91755 - 110106 £ per year.
Grafana Labs, the company behind the open observability cloud, is founded on the principles of open source, open standards, open ecosystems, and open culture. Grafana Cloud, our fully managed observability platform, is flexible and built for scale. With Grafana Cloud's actually useful AI, organizations can see, understand, and act on all their disparate data to move at the speed of their ambitions. Today, more than 35 million users and 7,000+ customers trust Grafana Labs to ensure reliability of their applications and systems, resolve incidents quickly, and optimize their telemetry to reduce noise and cost.
This is a fully remote position and we're considering candidates in the UK.
The Opportunity: Grafana Labs is building an Interactive Learning system, an open source, in-product learning experience that helps users learn and succeed without leaving Grafana. A central part of that vision is a personalized recommendation system that helps each user discover the next guide, action, or product experience most likely to help them succeed. We are hiring an ML Engineer to lead its evolution into an increasingly personalized, continuously improving system driven by real-time product behavior, content metadata, customer context, and experimentation.
What You’ll Be Doing:
- Evolve the Interactive Learning Plugin's recommendation system.
- Develop increasingly personalized approaches to candidate selection, ranking, sequencing, and next-best-action recommendations.
- Build and operate applied models.
- Define what recommendation quality means.
- Ship incremental improvements.
- Partner across disciplines.
What Makes You a Great Fit:
- Recommendation and personalization science: you have built recommendation, ranking, search, matching, propensity, or next-best-action systems.
- Applied model ownership: you have personally built, validated, monitored, and iterated on models used in a product or operational environment.
- You should also be a strong product thinker and technical communicator.
Bonus Points For:
- Experience with content, education, onboarding, or learning recommendation systems.
- Experience with SaaS product telemetry and customer-account data.
- Experience using warehouse-scale behavioral data.
- Experience with contextual bandits or other exploration strategies.
Compensation & Rewards: In the UK, the base compensation range for this role is GBP 91,755 - GBP 110,106. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process.
Why You’ll Thrive at Grafana Labs:
- 100% Remote, Global Culture.
- Scaling Organization.
- Transparent Communication.
- Innovation-Driven.
- Open Source Roots.
- Empowered Teams.
- Career Growth Pathways.
- Approachable Leadership.
- Passionate People.
- Balance is Key.
Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law.
Senior Machine Learning Engineer, Developer Advocacy | UK | Remote employer: Grafana Labs
Grafana Labs is an exceptional employer, offering a fully remote work environment that fosters a global culture of collaboration and innovation. With a strong commitment to employee growth, transparent communication, and a high-trust atmosphere, team members are empowered to tackle meaningful projects while enjoying a generous annual leave policy. Joining Grafana means being part of a passionate team dedicated to open-source values and the pursuit of excellence in AI-powered product analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer, Developer Advocacy | UK | Remote
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We think you need these skills to ace Senior Machine Learning Engineer, Developer Advocacy | UK | Remote
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Grafana Labs, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Grafana Labs. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Grafana Labs
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
