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- Tasks: Lead the development of a pioneering RLOps platform and integrate advanced ML frameworks.
- Company: Fast-growing AI infrastructure startup backed by top-tier VCs.
- Benefits: Flexible work environment, 6-month remote policies, and an annual learning budget.
- Why this job: Build groundbreaking tools in a high-impact field and stay at the forefront of AI research.
- Qualifications: Master’s or Ph.D. in Computer Science or 3+ years in reinforcement learning.
- Other info: Dynamic role with excellent career growth opportunities and support from AI recruiters.
The predicted salary is between 36000 - 60000 £ per year.
You will lead the development of a first-of-its-kind RLOps platform, designing scalable infrastructure for RL model training and LLM finetuning. By integrating advanced machine learning frameworks into an open-source ecosystem, you will provide critical tools for businesses to deploy reinforcement learning models effectively while staying at the forefront of AI research.
Location: London, UK
Why this role is remarkable:
- Opportunity to build pioneering RLOps infrastructure and open-source tools from the ground up in a high-impact field.
- Join a well-funded venture backed by top-tier VCs at the intersection of reinforcement learning and production-ready MLOps.
- Benefit from a highly flexible work environment with 6-month remote policies and a dedicated annual learning budget.
What you will do:
- Design and implement the architecture for a scalable RLOps platform and a robust open-source RL framework.
- Integrate diverse ML libraries and environments to support advanced model training, deployment, and lifecycle management.
- Stay current with the latest RL and MLOps advancements to incorporate cutting‑edge algorithms into the platform’s core.
The ideal candidate:
- Holds a Master’s or Ph.D. in Computer Science or has 3+ years of industry experience in reinforcement learning.
- Possesses deep expertise in PyTorch, Ray, or Gym, along with a strong background in hyperparameter optimization.
- Has proven experience building machine learning tooling, cloud‑based distributed infrastructure, and production deployment pipelines.
Reinforcement Learning Engineer (+ Equity) at fast-growing AI infrastructure startup in London employer: Jack & Jill/External Ats
Contact Detail:
Jack & Jill/External Ats Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Reinforcement Learning Engineer (+ Equity) at fast-growing AI infrastructure startup in London
✨Tip Number 1
Get to know Jack! He’s your go-to AI for understanding what you’re great at and what you want. A quick chat with him can help tailor your approach and make sure you’re on the right track.
✨Tip Number 2
Don’t just wait for job postings! Use our website to connect with Jack and explore opportunities that might not even be advertised yet. Networking is key, and we’ve got your back!
✨Tip Number 3
Prepare for your chat with Jill! Research the company and the role so you can show off your knowledge and enthusiasm. It’s all about making a great impression from the get-go.
✨Tip Number 4
Follow up after your conversation! A quick thank-you note or message can keep you fresh in Jill’s mind. Plus, it shows you’re genuinely interested in the role and the company.
We think you need these skills to ace Reinforcement Learning Engineer (+ Equity) at fast-growing AI infrastructure startup in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Reinforcement Learning Engineer role. Highlight your experience with PyTorch, Ray, or Gym, and any relevant projects that showcase your skills in building ML tooling and infrastructure.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about reinforcement learning and how your background makes you a perfect fit for this pioneering RLOps platform. Keep it engaging and personal.
Showcase Your Projects: If you've worked on any interesting RL projects or have contributions to open-source tools, make sure to mention them. This not only demonstrates your expertise but also shows your commitment to the field and innovation.
Apply Through Our Website: Don't forget to apply through our website! Click 'Talk to Jack' so he can get to know you better and help you stand out to Jill. We’re here to support you every step of the way in landing this exciting role!
How to prepare for a job interview at Jack & Jill/External Ats
✨Know Your Stuff
Make sure you brush up on reinforcement learning concepts, especially around RLOps and the tools mentioned in the job description like PyTorch and Ray. Being able to discuss your experience with these technologies will show that you're not just a good fit, but that you're genuinely passionate about the field.
✨Showcase Your Projects
Prepare to talk about specific projects you've worked on that relate to building machine learning tooling or cloud-based infrastructure. Highlight any challenges you faced and how you overcame them, as this will demonstrate your problem-solving skills and hands-on experience.
✨Stay Current
Familiarise yourself with the latest advancements in RL and MLOps. Mention any recent papers or breakthroughs that excite you during the interview. This shows that you're proactive and committed to staying at the forefront of AI research, which is crucial for this role.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's vision for their RLOps platform and how they plan to integrate open-source tools. This not only shows your interest in the role but also gives you a chance to assess if the company aligns with your career goals.
