At a Glance
- Tasks: Design and build a benchmarking system for evaluating AI solutions.
- Company: Callosum, a pioneering company in AI technology based in London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Exciting research environment with potential for impactful contributions.
- Why this job: Join a cutting-edge team and shape the future of AI evaluation.
- Qualifications: Experience in AI systems and strong analytical skills.
The predicted salary is between 81000 - 99000 £ per year.
Callosum in London is building a unified benchmarking system for evaluating agentic and algorithmic AI solutions.
You will design a harness to measure task success, quality, and robustness across motifs, agent topologies, and decomposition strategies, grounded in real commits and sandboxed grading.
This research hire builds and curates the evaluation framework, delivering proof points for customers and contributing to co-published benchmarks.
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Benchmarking Engineer for Agentic AI Systems (London) employer: Callosum
At Callosum, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our team thrives in a dynamic environment where tackling complex challenges is not just encouraged but celebrated, offering ample opportunities for professional growth and development. Located at the forefront of AI technology, we provide our employees with access to cutting-edge resources and a supportive community that values diverse perspectives and ideas.
StudySmarter Expert Advice🤫
We think this is how you could land Benchmarking Engineer for Agentic AI Systems (London)
✨Get Involved in Data Science Meetups
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Benchmarking Engineer for Agentic AI Systems (London) at Callosum.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Callosum.
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We think you need these skills to ace Benchmarking Engineer for Agentic AI Systems (London)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Callosum, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Callosum. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Callosum
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Callosum!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
