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- Tasks: Develop and enhance the Arena platform for reinforcement learning training and RLOps.
- Company: Join a fast-growing team at AgileRL, focused on cutting-edge AI technology.
- Benefits: Competitive salary, stock options, 30 days holiday, and flexible working arrangements.
- Why this job: Make a real impact in AI by developing innovative reinforcement learning tools.
- Qualifications: Master’s/Ph.D. in Computer Science or 3+ years of relevant experience required.
- Other info: Enjoy a dynamic work environment with regular socials and a learning budget.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a talented and experienced Machine Learning Engineer with a background in Reinforcement Learning to join our team. This engineer will contribute to the further development of Arena, a web-based software platform for reinforcement learning training and RLOps, and our open-source reinforcement learning library.
Responsibilities
- Collaborate with the team to understand requirements and design new features of the Arena platform and open-source framework.
- Develop scalable and reliable infrastructure to support reinforcement learning model training, LLM finetuning, model deployment, and management.
- Integrate existing machine learning frameworks and libraries into the platform and open-source framework, providing a range of algorithms, environments, and tools for reinforcement learning model development.
- Stay up-to-date with the latest advancements in AI, MLOps, reinforcement learning algorithms, tools, and techniques, and incorporate them into the platform as appropriate.
- Provide technical guidance and support to internal users and external customers using the Arena platform and open-source framework.
Requirements
- Master’s or Ph.D. degree in Computer Science, Engineering, or a related field, or 3+ years of relevant industry experience.
- Solid understanding of reinforcement learning algorithms and concepts, with hands-on experience in building and training reinforcement learning models.
- Strong programming skills, with experience using reinforcement learning and ML frameworks and libraries (e.g. PyTorch, TensorFlow, Ray, Gym, RLLib, SB3, TRL), and MLOps tools.
- Solid understanding of hyperparameter optimisation techniques and strategies.
- Experience in building machine learning platforms or tooling for industrial or enterprise settings.
- Proficiency in data management techniques, including storage, retrieval, and pre-processing of large-scale datasets.
- Familiarity with model deployment and management, including the development of APIs, deployment pipelines, and performance optimisation.
- Experience in designing and developing cloud-based infrastructure for distributed computing and scalable data processing.
- Deep understanding of software engineering and machine learning principles and best practices.
- Strong problem-solving and communication skills, and the ability to work independently as well as in a team environment.
Compensation
- Competitive salary + significant stock options.
- 30 days of holiday, plus bank holidays, per year.
- Flexible working from home and 6-month remote working policies.
- Enhanced parental leave.
- Learning budget of £500 per calendar year for books, training courses and conferences.
- Company pension scheme.
- Regular team socials and quarterly all-company parties.
- Bike2Work scheme.
Join the fast-growing AgileRL team and play a key role in the development of cutting-edge reinforcement learning tooling and infrastructure.
Machine Learning Engineer (RL) in City of London employer: AgileRL Ltd
Contact Detail:
AgileRL Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (RL) in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to reinforcement learning. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and algorithms. Practise coding challenges and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Machine Learning Engineer (RL) in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with reinforcement learning and relevant programming skills. We want to see how your background aligns with the role, so don’t be shy about showcasing your projects and achievements!
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 you can contribute to our Arena platform. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects: If you've worked on any cool reinforcement learning projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to see what you've done and how it relates to the role.
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’s super easy – just follow the prompts and submit your materials!
How to prepare for a job interview at AgileRL Ltd
✨Know Your Algorithms
Make sure you brush up on your reinforcement learning algorithms before the interview. Be ready to discuss how you've applied them in past projects, and think of specific examples where you’ve tackled challenges using these techniques.
✨Showcase Your Coding Skills
Since strong programming skills are a must, be prepared to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges related to ML frameworks like PyTorch or TensorFlow to show off your expertise.
✨Understand the Arena Platform
Familiarise yourself with the Arena platform and its features. Knowing how it integrates with existing ML frameworks will help you discuss how you can contribute to its development and improvement during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects and future goals. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values and work style.