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For Companies At a Glance
- Tasks: Develop groundbreaking algorithms for real-time learning and decision-making in dynamic environments.
- Company: Join a fast-growing start-up focused on building cutting-edge agentic AI solutions.
- Benefits: Enjoy competitive salary, equity, flexible work options, and access to the latest tech.
- Why this job: Shape the future of AI while collaborating with passionate innovators in a dynamic environment.
- Qualifications: PhD or equivalent in Machine Learning or related fields; expertise in RL algorithms required.
- Other info: Opportunity to publish research at top-tier conferences and contribute to the global AI community.
The predicted salary is between 43200 - 72000 £ per year.
🚀 Join Us: Research Scientist – Online Reinforcement Learning (RL) at an Agentic AI Start-Up! 🌟
Are you ready to revolutionize the future of intelligent agents? We\’re an Agentic AI start-up on a mission to build the next generation of autonomous systems capable of real-time learning, adaptation, and decision-making. If you’re passionate about Online Reinforcement Learning and want to shape the frontier of AI, we’d love to hear from you!
About Us
We are a well-funded, ambitious, fast-growing start-up building AI agents that can learn, adapt, and thrive in dynamic, interactive environments. Our vision is to empower businesses and individuals with cutting-edge, agentic AI solutions that redefine how machines interact with the world.
The Role
As a Research Scientist in Online Reinforcement Learning, you will:
- Innovate: Develop groundbreaking algorithms for real-time learning and decision-making in dynamic, multi-agent systems.
- Collaborate: Work closely with a team of researchers and engineers to create scalable solutions that deliver real-world impact.
- Experiment: Lead experimental projects to address challenges like stability, data efficiency, and exploration in online RL.
- Productize AI: Translate research insights into deployable AI systems for robotics, gaming, autonomous platforms, and more.
- Share Knowledge: Publish research at top-tier conferences (e.g., NeurIPS, ICML, ICLR) and contribute to the global AI community.
What You’ll Bring
- PhD or equivalent in Machine Learning, Reinforcement Learning, Computer Science, or related fields.
- Expertise in RL algorithms (e.g., PPO, A3C, DQN) and their application to dynamic environments.
- Proven Research Impact: Strong publication record in top conferences/journals and a passion for advancing AI.
- Technical Skills: Proficiency in Python, RL frameworks (PyTorch/TensorFlow), and cloud-based ML tools.
- Start-Up Mindset: A proactive, problem-solving attitude and a love for tackling challenges in fast-paced environments.
- Visionary Thinking: A deep interest in agentic AI and its potential to transform industries.
Why Join Us?
- Impactful Work: Shape the future of agentic AI in industries like autonomous vehicles, robotics, and intelligent systems.
- Ownership: Be part of a start-up where your ideas and contributions directly drive our success.
- Cutting-Edge Tech: Access to the latest tools, resources, and computational infrastructure.
- Growth Opportunities: Thrive in a collaborative, growth-focused culture that values curiosity and innovation.
- Start-Up Perks: Competitive salary, meaningful equity, flexible work options, and a chance to grow with us.
Our Mission
At our core, we’re driven by the belief that intelligent agents can reshape the way we live, work, and explore. Join us on our journey to build a future where AI systems are not just tools but partners in discovery and creation.
Reinforcement Learning Scientist employer: Stealth AI Startup
Contact Detail:
Stealth AI Startup Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Reinforcement Learning Scientist
✨Tip Number 1
Familiarize yourself with the latest advancements in Online Reinforcement Learning. Follow key researchers and organizations in the field on social media and engage with their content to stay updated and show your passion during interviews.
✨Tip Number 2
Participate in relevant online forums and communities, such as GitHub or specialized AI groups. Contributing to discussions or projects can help you network with professionals in the field and demonstrate your expertise.
✨Tip Number 3
Prepare to discuss your previous research and its impact in detail. Be ready to explain how your work aligns with the goals of our start-up and how it can contribute to the development of agentic AI solutions.
✨Tip Number 4
Showcase your start-up mindset by highlighting experiences where you've tackled challenges in fast-paced environments. This will demonstrate your adaptability and problem-solving skills, which are crucial for our team.
We think you need these skills to ace Reinforcement Learning Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your expertise in reinforcement learning algorithms and any relevant projects you've worked on. Emphasize your publication record and technical skills, particularly in Python and RL frameworks.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for agentic AI and how your background aligns with the company's mission. Mention specific experiences that demonstrate your problem-solving attitude and ability to innovate in fast-paced environments.
Showcase Research Impact: Include details about your research contributions, especially any publications in top-tier conferences like NeurIPS or ICML. Highlight how your work has advanced the field of AI and its practical applications.
Express Your Vision: In your application, convey your visionary thinking regarding the future of intelligent agents. Discuss how you see your role contributing to the development of autonomous systems and the impact they can have across various industries.
How to prepare for a job interview at Stealth AI Startup
✨Showcase Your Research Impact
Be prepared to discuss your previous research and publications in detail. Highlight how your work has contributed to the field of reinforcement learning and any innovative algorithms you've developed.
✨Demonstrate Technical Proficiency
Make sure to showcase your skills in Python and familiarity with RL frameworks like PyTorch or TensorFlow. You might be asked to solve a coding problem or discuss your experience with cloud-based ML tools.
✨Emphasize Collaboration Skills
Since the role involves working closely with a team, be ready to share examples of past collaborations. Discuss how you’ve worked with others to tackle complex problems and drive projects forward.
✨Express Your Vision for Agentic AI
Articulate your passion for agentic AI and its potential impact on various industries. Share your thoughts on future trends in AI and how you envision contributing to this evolving field.
