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- Tasks: Develop and implement cutting-edge AI algorithms for autonomous robots.
- Company: Exciting robotics start-up focused on innovative industrial solutions.
- Benefits: Competitive salary up to £150k, career growth, and a collaborative team environment.
- Why this job: Join a talented team and make a real impact in the world of robotics.
- Qualifications: Expertise in machine learning frameworks and robotics experience required.
- Other info: Work in London with opportunities for research and innovation.
The predicted salary is between 72000 - 108000 £ per year.
Base pay rangeDirect message the job poster from Cubiq Recruitment2 Positions: Machine Learning Engineer & Machine Learning ResearcherMy client is a scaling robotics start-up that is creating autonomous industrial robots capable of handling intricate, dexterous tasks. They\’re looking for Senior ML Engineers who want the freedom to bridge the gap between state-of-the-art research in embodied AI and real-world systems.You\’ll be joining a team of accomplished roboticists with excellent PhDs, high-impact research, and industrial know-how, who will help nurture and develop you to the next level!Salary: Up to £150kLocation: LondonWhat You\’ll Be Doing (Machine Learning Engineer): Implement and scale state-of-the-art AI algorithms to be deployed on real-world robotic systemsBuild robust data pipelines and work with multi-modal sensor dataCollaborate with a talented team of researchers to improve and refine algorithms for real-world tasksEnsure the scalability and maintainability of production systems, with a strong focus on (low-level) MLOpsWhat You\’ll Be Doing (Machine Learning Researcher): Conduct groundbreaking research to develop new algorithms and models for roboticsWork on advanced learning approaches such as reinforcement learning and imitation learningContribute to creating multi-robot systems and cross-embodiment learning techniquesDrive innovation by publishing research and attending top conferencesExpertise in PyTorch or TensorFlow, distributed computing, and multi-GPU trainingRobotics experience, particularly in reinforcement/ imitation learningExperience in cloud infrastructure (AWS, GCP, or Azure) and containerizationAbility to translate research papers into deployable systemsResearcher Background: PhD or advanced degree in Robotics, Machine Learning, or a similar fieldExperience with top-tier conferences like CoRL, ICRA, RSS, ICML, ICLR, NeurIPSStrong knowledge of reinforcement learning, imitation learning, and real-world deploymentSeniority level Mid-Senior levelEmployment type Full-timeJob function Research and EngineeringRobotics Engineering and Computers and Electronics ManufacturingReferrals increase your chances of interviewing at Cubiq Recruitment by 2xLondon, England, United Kingdom
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Senior Machine Learning Engineer employer: Cubiq Recruitment
Contact Detail:
Cubiq Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the robotics and AI community, especially those who work at companies you're interested in. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving PyTorch or TensorFlow. Real-world examples of your work can make you stand out in interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your algorithms and MLOps knowledge. Practice coding challenges and be ready to discuss how you've tackled complex problems in your past roles.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience with AI algorithms and robotics. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or research!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about bridging research and real-world applications in robotics. Let us know what excites you about the role and how you can contribute to our team.
Showcase Your Projects: If you've worked on any cool projects, especially those involving PyTorch, TensorFlow, or multi-modal sensor data, make sure to mention them! We love seeing practical applications of your skills, so include links or descriptions of your work.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at Cubiq Recruitment
✨Know Your Algorithms
Make sure you brush up on the latest AI algorithms, especially those related to reinforcement and imitation learning. Be ready to discuss how you've implemented these in past projects and how they can be applied to real-world robotic systems.
✨Showcase Your Projects
Prepare to talk about your previous work with PyTorch or TensorFlow, particularly any projects involving multi-GPU training or cloud infrastructure. Bring examples that highlight your ability to build robust data pipelines and how you've tackled challenges in deploying machine learning models.
✨Collaborative Spirit
This role involves working closely with a team of researchers and roboticists. Be prepared to discuss how you've collaborated in the past, what you learned from those experiences, and how you can contribute to a team environment focused on innovation and research.
✨Research and Conferences
If you've attended or published at top-tier conferences, make sure to mention this during your interview. Discussing your insights from these events can demonstrate your commitment to staying at the forefront of the field and your ability to translate cutting-edge research into practical applications.
