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- Tasks: Develop and implement cutting-edge Recommender Systems for retail using advanced AI techniques.
- Company: Join a stealth-mode VC-backed startup focused on behavioural AI and innovative solutions.
- Benefits: Enjoy hybrid work with at least 3 days in our vibrant London office and competitive perks.
- Why this job: Be part of a dynamic team, working on impactful AI solutions that shape the future of retail.
- Qualifications: MSc in Computer Science or related field; hands-on experience with Recommender Systems required.
- Other info: Bonus points for expertise in deep learning frameworks and generative AI.
The predicted salary is between 43200 - 72000 £ per year.
We are a VC-backed startup focused on behavioural AI, currently in stealth mode. We are building for retail with a focus on Recommendation Systems, Reinforcement Learning and GenAI. We are looking for an Applied AI Scientist with deep experience in advanced Recommender Systems to work with our team of industry leading domain experts and engineers.
Areas of focus:
- Design and implement scalable Recommender Systems.
- Translate latest Recommender Systems advances into impactful solutions and products, from MVPs to fully deployed systems.
- Optimise machine learning models for performance in modern environments (e.g., distributed clusters, GPUs).
Requirements:
- Hands on experience: Implemented Recommender System solutions in commercial context.
- Education: MSc in Computer Science, Machine Learning, or a closely related field.
- Strong foundation in machine learning and deep learning algorithms (e.g., deep neural networks, supervised/unsupervised learning, predictive analysis, forecast modelling).
- Excellent Python programming skills with experience in developing and debugging production-level code.
Bonus points:
- Expertise with PyTorch and HuggingFace transformers.
- Strong practical understanding of LLMs and transformers.
- PhD in a related field.
- Reinforcement Learning knowledge.
Applied AI Scientist (Recommender Systems) employer: algo1
Contact Detail:
algo1 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI Scientist (Recommender Systems)
✨Tip Number 1
Network with professionals in the AI and machine learning community. Attend meetups, conferences, or webinars focused on recommender systems and behavioural AI to connect with industry experts and learn about potential job openings.
✨Tip Number 2
Showcase your hands-on experience by working on personal projects or contributing to open-source projects related to recommender systems. This practical experience can set you apart and demonstrate your skills to potential employers.
✨Tip Number 3
Stay updated on the latest advancements in recommender systems and generative AI. Follow relevant research papers, blogs, and online courses to deepen your knowledge and be prepared to discuss these topics during interviews.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and algorithm questions specifically related to machine learning and recommender systems. Use platforms like LeetCode or HackerRank to sharpen your skills.
We think you need these skills to ace Applied AI Scientist (Recommender Systems)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Recommender Systems and machine learning. Use specific examples of projects you've worked on, especially those that demonstrate your skills in Python and deep learning frameworks like PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your passion for behavioural AI and how your background aligns with the company's focus. Mention any relevant projects or experiences that showcase your ability to develop scalable solutions and optimise performance.
Showcase Relevant Skills: Clearly outline your technical skills related to machine learning, deep learning, and programming. Highlight your hands-on experience with Recommender Systems and any knowledge of reinforcement learning, as these are key areas for the role.
Proofread and Edit: Before submitting your application, take the time to proofread your documents. Check for any grammatical errors or typos, and ensure that your application is clear and concise. A polished application reflects your attention to detail.
How to prepare for a job interview at algo1
✨Showcase Your Practical Experience
Be prepared to discuss specific projects where you've implemented Recommender Systems. Highlight the challenges you faced and how you overcame them, as this will demonstrate your hands-on experience in a commercial context.
✨Demonstrate Your Technical Skills
Make sure to brush up on your Python programming skills and be ready to solve coding problems during the interview. Familiarity with deep learning frameworks like PyTorch and HuggingFace transformers will give you an edge, so mention any relevant projects or experiences.
✨Understand the Latest Trends
Stay updated on the latest advancements in Recommender Systems and Generative AI. Be prepared to discuss how these trends can be applied to the company's goals, showing that you're not just knowledgeable but also forward-thinking.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially in performance optimisation of machine learning models. Practice explaining your thought process clearly, as this will showcase your analytical skills and ability to work under pressure.
