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- Tasks: Lead machine learning validation for high-stakes computer vision projects in aviation, mobility, and robotics.
- Company: Join Safe Intelligence, a pioneering company dedicated to making AI safe and reliable for everyone.
- Benefits: Enjoy flexible holidays, mentoring opportunities, and a collaborative work culture with regular team events.
- Why this job: Make a real impact by solving complex problems and advancing AI technology for global engineers.
- Qualifications: Experience with machine vision models and proficiency in Python and data science libraries required.
- Other info: We value diverse backgrounds and support ongoing learning for all team members.
The predicted salary is between 36000 - 60000 £ per year.
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Safe Intelligence is on a mission to make AI safe and reliable for anyone to use. To help us succeed, our team is looking for Machine Learning Specialists, and we’re hoping it’s you!
In this role, you’ll play a leading role in helping both customers with their ML validation challenges and in helping drive our product forward with insights on how to build the best validation solutions for high-stakes machine vision problems.The specific focus of this position is on ML-based computer vision in high-stakes applications in Aviation, Mobility, Robotics and Edge Devices.
The role has significant customer & user-facing elements working on real world problems to help ML teams (R&D and Product within other organizations) improve the quality of their models. In addition you will also work closely with the Safe Intelligence R&D team to help improve the company’s tools based on the challenges you see in your domains of expertise. This can range from inputs to product to working on the product itself.
Working knowledge or contributions to state-of-the-art machine vision models including object detectors as used in applications is required. Previous knowledge of Machine Learning verification isn’t required, but a solid knowledge of existing testing practices, metrics, state-of-the-art training and validation methods are extremely valuable.
We’re looking forward to having you on board!
Responsibilities : As a Safe Intelligence Machine Learning Specialist – Computer Vision , you will:
- Work closely with customers and end-users to understand their machine vision models and help them assess performance. Generally these will be R&D and product teams at customer organisations including leading teams in major companies in Aviation, Mobility, Robotics, and Edge Devices
- Implement prototypes, use cases, and solutions that apply the algorithms developed at Safe Intelligence to address user-specific problems, particularly in the field of machine vision for Aviation, Mobility, Robotics and Edge Devices.
- Conduct experiments to evaluate various approaches and weigh their respective trade-offs.
- Coordinate with the research and platform teams to guide future development based on use-case specific challenges.
- Contribute to the development of an efficient and scalable package for performing verification and robust learning.
Requirements : The technical requirements for the role are:
- Experience in training, evaluating and deploying Machine Vision models, including standard architectures such as Yolo, Vision Transformer architectures, and Eva.
- An in-depth understanding of machine learning models enabling you to train such models to high performance and modify/tune their architecture based on given constraints.
- Experience talking to stakeholders in these models to understand their requirements and guiding them through what is and is not possible or desirable in a model.
- Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch.
- Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall, F1 scores and others.
Additional beneficial experience includes:
- Familiarity with best practice in Machine Learning workflows and MLOps tools.
- Technical experience in developing non-ML solutions in the Aviation, Mobility, Edge Devices, and/or Robotics industries.
At a personal level we’re also looking for some who is:
- Passionate about helping engineering teams achieve their AI and ML goals.
- Excited about interacting with others and digging in to help solve their problems collaboratively.
- Technical and constantly in a state of learning.
- Able to communicate clearly and efficiently with a variety of audiences including developers, customers, researchers, partners and executives.
- Fearless in getting \”hands-on\” with technology and execution.
- Knowledgeable about modern software engineering processes.
- Comfortable with ambiguity with a drive for clarity.
- Collaborative with, and respectful of others on the team.
- Honest, straightforward and caring about each other’s well being.
Why Safe Intelligence is for you :
We strongly believe AI can bring great benefits to individuals and society, but these will only be achieved if the systems we build are safe to use. To meet this need, we are developing advanced deep validation techniques and tools that allow AI/ML engineers world-wide to validate the robustness of their models, as well as repair the fragilities that they discover.
By joining us, you’ll be able to help advance the techniques, bring advanced technologies to AI/ML engineers worldwide and contribute to our shared mission to realise successful and reliable AI.
Grow with us!
If you think you can bring something special to this role, please apply even if you do not meet all listed criteria. Safe Intelligence is exploring uncharted waters, and finding the right crewmates is important to us. We support ongoing learning for the whole team, ranging from individual mentorship to internal seminars and support for sector and technology-specific upskilling.
Safe Intelligence provides competitive compensation based on role and candidate experience. We aim to be competitive with pay rates.
Company benefits for all roles include:
- Mentoring, learning, and development allowance
- Regular team social and work events
- Flexible and generous holidays. We work hard and encourage everyone to take time off to recharge and enjoy other aspects of our lives.
Equality and Inclusion
We are proud to be an equal-opportunity employer and work hard to create an environment where people of diverse backgrounds and life experiences can thrive. The team is highly collaborative and meritocratic. Great ideas come from everywhere, and we strive to make it easy for people to express themselves and be heard.
Location & Office Culture
Safe Intelligence is based in London, UK, and we’re focused on building the initial team here. We highly value the ability to work flexibly and remotely at times, but we also have a strong belief that regular in-office interactions make for a much more fulfilling and productive work experience.
Our company culture combines optimism for the future (hard problems can be solved with the right effort), speed of iteration (the best ideas come from many ideas tested), and rigour in what matters (correctness and precision are critical for safety).
Come and join us to add your skills and passion to the future of Safe Artificial Intelligence!
Seniority level
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Seniority level
Entry level
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Employment type
Full-time
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Job function
Engineering and Information Technology
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Industries
Software Development
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Machine Learning Specialist - Computer Vision employer: Safe Intelligence
Contact Detail:
Safe Intelligence Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Specialist - Computer Vision
✨Tip Number 1
Familiarise yourself with the latest advancements in machine vision models, particularly those like Yolo and Vision Transformers. Being able to discuss these technologies confidently during interviews will demonstrate your expertise and passion for the field.
✨Tip Number 2
Engage with the community by participating in forums or attending meetups related to machine learning and computer vision. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to showcase your problem-solving skills by thinking of real-world applications where you've successfully implemented machine vision solutions. Be ready to discuss specific challenges you faced and how you overcame them.
✨Tip Number 4
Stay updated on the latest trends in MLOps and validation frameworks. Understanding how these practices integrate with machine learning will not only enhance your knowledge but also show your commitment to best practices in the field.
We think you need these skills to ace Machine Learning Specialist - Computer Vision
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and computer vision. Focus on specific projects or roles where you've trained, evaluated, or deployed machine vision models, especially using architectures like Yolo or Vision Transformers.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and machine learning. Mention how your skills align with the responsibilities outlined in the job description, particularly your experience with customer-facing roles and collaboration with R&D teams.
Showcase Technical Skills: Clearly list your technical skills related to Python and data science libraries such as NumPy, pandas, TensorFlow, and PyTorch. Provide examples of how you've used these tools in past projects to solve real-world problems.
Demonstrate Problem-Solving Abilities: Include examples in your application that demonstrate your ability to tackle complex challenges in machine vision. Discuss any experiments you've conducted to evaluate different approaches and how you coordinated with teams to guide development.
How to prepare for a job interview at Safe Intelligence
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine vision models, particularly those like Yolo and Vision Transformers. Highlight specific projects where you've trained, evaluated, or deployed these models, as this will demonstrate your hands-on expertise.
✨Understand the Customer's Needs
Since the role involves significant customer interaction, practice articulating how you would approach understanding a client's machine vision challenges. Think of examples where you've successfully communicated technical concepts to non-technical stakeholders.
✨Familiarise Yourself with Validation Metrics
Brush up on key validation and evaluation metrics such as Accuracy, Recall, and F1 scores. Be ready to discuss how these metrics influence model performance and decision-making in high-stakes applications.
✨Demonstrate Collaborative Spirit
Safe Intelligence values teamwork, so be prepared to share examples of how you've worked collaboratively in past roles. Discuss how you handle ambiguity and drive clarity in team settings, as this aligns with their company culture.
