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- Tasks: Join us to innovate and optimise machine learning models for retail shopping.
- Company: We're a stealth VC-backed startup revolutionising retail with behavioural AI.
- Benefits: Enjoy competitive pay, equity options, and a collaborative work culture.
- Why this job: Make a real impact on shopping experiences using cutting-edge AI technology.
- Qualifications: 3-5+ years in applied machine learning; MSc required; Python skills essential.
- Other info: Work with industry experts and tackle exciting challenges in a dynamic environment.
The predicted salary is between 48000 - 72000 £ per year.
We are a VC-backed startup focused on behavioural AI, currently in stealth. We are building for retail with a focus on Recommendation Systems, Reinforcement Learning and Generative AI. Our platform is designed from the ground up — no legacy, no patchwork systems — just a clean slate and a clear vision. Our mission is to build products that customers love by harnessing cutting-edge AI to transform their shopping experience.
We are looking for a Senior Research Engineer with experience in advanced machine learning systems to work with our team of industry leading domain experts and engineers to build foundation models for retail shopping.
Key Responsibilities:- Translate latest ML advances into impactful solutions, validate their effectiveness, and deploy them to production systems.
- Innovate upon state-of-the-art ML research applied to consumer personalisation.
- Optimise machine learning models for performance in cloud environments (e.g., distributed clusters, GPUs).
- 3-5+ years implementing applied machine learning research in a production setting
- MSc in Computer Science, Machine Learning, or a closely related field
- Strong foundation in machine learning and deep learning algorithms (e.g., transformers, GNNs, supervised/unsupervised learning, reinforcement learning, deep neural networks)
- Excellent Python programming skills with experience in developing and debugging production-level code
- Proven experience in recommender systems, behavioural AI, and/or reinforcement learning.
- Building data pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt).
- PhD in Computer Science, Machine Learning, or a closely related field
- Opportunity to build technology that will transform millions of shopping experiences
- Real ownership and impact in shaping our product and company direction
- A dynamic and collaborative work environment
- A chance to work with cutting-edge technologies and solve challenging problems
- Competitive compensation
- Equity in a rapidly growing company
Senior Research Engineer (City of London) employer: algo1
Contact Detail:
algo1 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Research Engineer (City of London)
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning, particularly in areas like recommendation systems and reinforcement learning. This will not only help you understand the company's focus but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your experience with cloud environments and optimising machine learning models. Be prepared to discuss specific projects where you've successfully deployed models in production, as this aligns closely with the role's key responsibilities.
✨Tip Number 3
Network with professionals in the behavioural AI and retail sectors. Attend relevant meetups or webinars to connect with industry experts, which could lead to valuable insights and potential referrals for the position.
✨Tip Number 4
Prepare to demonstrate your Python programming skills through practical examples. Consider working on a small project that showcases your ability to develop and debug production-level code, as this will be crucial in proving your technical capabilities.
We think you need these skills to ace Senior Research Engineer (City of London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and any relevant projects you've worked on. Focus on your skills in Python programming and any specific algorithms or technologies mentioned in the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for behavioural AI and how your background aligns with the company's mission. Mention specific experiences that demonstrate your ability to innovate in machine learning and your understanding of consumer personalisation.
Showcase Relevant Projects: If you have worked on projects related to recommendation systems or reinforcement learning, be sure to include them in your application. Describe your role, the challenges faced, and the impact of your work.
Highlight Continuous Learning: Mention any recent courses, certifications, or conferences you've attended that relate to advanced machine learning. This shows your commitment to staying updated with the latest trends and technologies in the field.
How to prepare for a job interview at algo1
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with machine learning algorithms and frameworks. Highlight specific projects where you've implemented advanced techniques, especially in production settings, as this will demonstrate your capability to translate theory into practice.
✨Demonstrate Problem-Solving Skills
Expect to face technical challenges during the interview. Practice explaining your thought process when tackling complex problems, particularly those related to optimisation and deployment of machine learning models in cloud environments.
✨Familiarise Yourself with Their Focus Areas
Research the company's emphasis on recommendation systems and behavioural AI. Be ready to discuss how your background aligns with their mission and how you can contribute to innovating their product offerings.
✨Prepare Questions About Their Technology Stack
Show your interest by asking insightful questions about the tools and technologies they use, such as Apache Spark or Kafka. This not only demonstrates your knowledge but also your enthusiasm for the role and the company’s vision.
