At a Glance
- Tasks: Engage with customers to design AI evaluations and integrate workflows into production.
- Company: Join Callosum, a pioneering Intelligent Systems Company at the forefront of technology.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Be part of a dynamic team that values innovation and impact.
- Why this job: Shape the future of AI by collaborating with top engineers and researchers.
- Qualifications: Experience in AI and strong collaboration skills are essential.
The predicted salary is between 72000 - 88000 £ per year.
Callosum is an Intelligent Systems Company building a unified stack for heterogeneous accelerators and frontier silicon.
The Applied AI team engages directly with customer engineering teams to understand AI workloads, design evaluations, and integrate optimized workflows into production pipelines.
As an early member, you’ll shape the methodology, tooling, and practices, collaborating with platform and research teams to scale the function and impact across customers.
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Applied AI Engineer — Customer Deployments & Evaluation employer: UNCOVER
Join a prestigious UK law firm that values its employees and fosters a collaborative work culture in the vibrant cities of London and Brighton. With a strong commitment to professional development, you will have access to excellent growth opportunities while working on complex, high-profile matters alongside experienced professionals. The firm's supportive environment encourages mentorship and innovation, making it an ideal place for those seeking meaningful and rewarding employment in the legal sector.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Engineer — Customer Deployments & Evaluation
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We think you need these skills to ace Applied AI Engineer — Customer Deployments & Evaluation
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!
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Craft a Tailored Cover Letter:For a full-time role at UNCOVER, 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 UNCOVER. 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 UNCOVER
✨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!
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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 UNCOVER!
✨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.
