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- Tasks: Develop and optimise cutting-edge AI models for real-world applications.
- Company: Ultralytics is a leader in open-source AI innovation, shaping the future of Vision AI.
- Benefits: Enjoy a vibrant office environment and the chance to work with top-tier talent.
- Why this job: Join a passionate team making a global impact in AI technology.
- Qualifications: Must have relevant experience in machine learning and a strong passion for AI.
- Other info: Position based in London; legal work authorization in the UK required.
The predicted salary is between 43200 - 72000 £ per year.
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Founder & CEO at Ultralytics | Democratizing vision AI
At Ultralytics, we relentlessly drive innovation in AI, building the world\’s leading open-source models. We\’re looking for passionate individuals obsessed with AI, eager to make a global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI.
Location and Legalities
This full-time Machine Learning Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa sponsorship.
What You\’ll Do
As a Machine Learning Engineer at Ultralytics, you will be at the forefront of developing and refining our world-class Ultralytics YOLO models. You will work on the entire lifecycle of our models, from research and development to high-performance deployment. Key responsibilities include:
- Developing, training, and validating state-of-the-art models for a variety of computer vision tasks, including detection, segmentation, and classification.
- Writing highly efficient, scalable, and production-ready code in Python using the PyTorch framework.
- Optimizing models for high-performance inference on diverse hardware using tools like NVIDIA TensorRT, OpenVINO, and ONNX.
- Managing and processing large-scale datasets and implementing advanced data augmentation strategies.
- Designing and maintaining robust CI/CD pipelines with GitHub Actions for automated model training, testing, and benchmarking.
- Collaborating with our research and engineering teams to implement cutting-edge techniques and contribute to our open-source repositories.
- Engaging with our global community by creating documentation, tutorials, and supporting users to solve real-world problems with our technology.
Your expertise will be critical in advancing the capabilities of our models and supporting Ultralytics\’ mission to make AI easy and accessible for everyone.
️ Skills and Experience
- 5+ years of professional experience in Machine Learning Engineering or a similar role.
- Deep expertise in Python and deep learning frameworks, with a strong preference for PyTorch.
- Proven experience with computer vision and a strong understanding of model architectures like transformers and CNNs.
- Hands-on experience with model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO.
- Proficiency with CUDA programming and optimizing code for GPU acceleration.
- Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment.
- Experience contributing to major open-source projects is a significant advantage.
Cultural Fit – Intensity Required
Ultralytics is a high-performance environment for world-class talent obsessed with achieving extraordinary results. We operate at a relentless pace, demanding exceptional dedication and an unwavering commitment to excellence, guided by our mission, vision, and values. Our team thrives on audacious goals and absolute ownership. This is not a conventional workplace. If your priority is predictable comfort or a standard work-life balance over the relentless pursuit of progress, Ultralytics is not for you. We seek driven individuals prepared for the profound personal investment required to make a defining contribution to the future of AI.
Compensation and Benefits
- Competitive Salary: Highly competitive based on experience.
- Startup Equity: Participate directly in our company\’s growth and success.
- Hybrid Flexibility: 3 days per week in our brand-new office – 2 days remote.
- Generous Time Off: 24 days vacation, your birthday off, plus local holidays.
- Flexible Hours: Tailor your working hours to suit your productivity.
- Tech: Engage with cutting-edge AI projects.
- Gear: Brand-new Apple MacBook and Apple Display provided.
- Team: Become part of a supportive and passionate team environment.
If you are driven to redefine the capabilities of machine learning and eager to make a significant impact, Ultralytics offers an exceptional career opportunity.
Seniority level
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Seniority level
Associate
Employment type
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Employment type
Full-time
Job function
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Job function
Research and Science
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Industries
Software Development and Information Services
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Machine Learning Engineer employer: Ultralytics
Contact Detail:
Ultralytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, especially those related to open-source models. This knowledge will not only help you stand out during interviews but also demonstrate your genuine passion for the field.
✨Tip Number 2
Engage with the AI community by attending meetups, webinars, or conferences. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals for the position at Ultralytics.
✨Tip Number 3
Showcase your skills through personal projects or contributions to open-source initiatives. Having a portfolio that highlights your practical experience with machine learning can significantly boost your chances of landing the job.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and algorithm questions relevant to machine learning. Being well-prepared will help you feel more confident and perform better during the interview process.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Read the job description carefully to understand the specific skills and experiences Ultralytics is looking for in a Machine Learning Engineer. Tailor your application to highlight relevant experience in AI and machine learning.
Showcase Your Passion: In your cover letter or personal statement, express your enthusiasm for AI and how it drives you. Mention any projects or contributions you've made in the field of machine learning that demonstrate your commitment and passion.
Highlight Relevant Skills: Make sure to include technical skills that are pertinent to the role, such as programming languages (Python, TensorFlow, etc.), data analysis, and model development. Use specific examples to illustrate your expertise.
Proofread Your Application: Before submitting, thoroughly proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects attention to detail, which is crucial in a technical role like this.
How to prepare for a job interview at Ultralytics
✨Show Your Passion for AI
Make sure to express your enthusiasm for artificial intelligence during the interview. Share specific projects or experiences that highlight your obsession with AI and how you’ve contributed to innovative solutions in the field.
✨Demonstrate Technical Proficiency
Be prepared to discuss your technical skills in machine learning, including algorithms, frameworks, and tools you've used. Consider bringing examples of your work or projects that showcase your expertise and problem-solving abilities.
✨Understand Ultralytics' Vision
Research Ultralytics and their open-source models before the interview. Familiarise yourself with their products and vision for Vision AI, so you can align your answers with their goals and demonstrate your fit for the team.
✨Prepare for a Dynamic Environment
Since the role is in a high-energy environment, be ready to discuss how you handle fast-paced situations and adapt to change. Share examples of how you've thrived in similar settings and contributed positively to team dynamics.
