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For Companies At a Glance
- Tasks: Join our AI Lab to develop data pipelines and optimise performance for cutting-edge AI solutions.
- Company: Be part of a leading UK enterprise AI organisation transforming how businesses leverage machine intelligence.
- Benefits: Enjoy a steep learning curve, unmatched research experience, and the chance to work with top experts.
- Why this job: This role offers a unique opportunity to innovate in AI while collaborating with brilliant minds.
- Qualifications: Bachelor’s or Master’s in computer science, engineering, maths, or physics; programming skills required.
- Other info: Work 40 hours a week in a dynamic, high-growth environment focused on AI excellence.
The predicted salary is between 43200 - 72000 £ per year.
Our client, a London based Technology and Data Engineering leader, has an opportunity in a high growth AI Lab for an ‘AI Engineering Researcher’. A UK based 'Enterprise' Artificial Intelligence organisation focuses on helping accelerate their clients' journey towards becoming 'AI-Optimal' - starting with significantly enhancing its abilities in leveraging AI & machine intelligence to outperform traditional competition. The firm builds upon its rapidly expanding research team of exceptional PhD computer scientists, software engineers, mathematicians & physicists, to use a unique multi-disciplinary approach to solving enterprise-AI problems.
Principal Activities of role:
- Data Pipeline Development: Design, develop, and maintain ETL processes to efficiently ingest data from various sources into data warehouses or data lakes.
- Data Integration and Management: Integrate data from disparate sources, ensuring data quality, consistency, and security across systems. Implement data governance practices and manage metadata.
- System Architecture: Design robust, scalable, and high-performance data architectures using cloud-based platforms (e.g., AWS, Google Cloud, Azure).
- Performance Optimization: Monitor, troubleshoot, and optimize data processing workflows to improve performance and reduce latency.
Typical background:
- Bachelor’s or Master’s degree in computer science/engineering/Math/Physics, plus one or more of the following:
- Proficiency in programming languages such as Python, Java, or Scala.
- Strong experience with SQL and database technologies (incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases).
- Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage.
- Familiarity with data warehousing solutions and cloud data platforms.
- Background in building applications wrapped around AI/LLM/mathematical models.
- Ability to scale up algorithms to production.
Key Proposition: This role offers the opportunity to be part of creating world-class engineered solutions within Artificial Intelligence / Machine Learning, with a steep learning curve and an unmatched research experience.
Time Commitments: 100% (average 40 hours per week)
Contact Detail:
Placed Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineering Researcher (London Area)
✨Tip Number 1
Familiarise yourself with the latest trends in AI and data engineering. Follow industry leaders on social media, read relevant research papers, and engage in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the AI and data engineering sectors. Attend meetups, webinars, or conferences where you can connect with people who work in similar roles. Building relationships can lead to valuable insights and potential referrals for the position.
✨Tip Number 3
Showcase your technical skills through personal projects or contributions to open-source initiatives. Having a portfolio that demonstrates your proficiency in programming languages and data tools will set you apart from other candidates and provide concrete examples of your capabilities.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and system design problems related to data pipelines and architectures. Use platforms like LeetCode or HackerRank to sharpen your skills, ensuring you're ready to tackle any technical questions that may arise during the interview process.
We think you need these skills to ace AI Engineering Researcher (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI, data engineering, and programming languages like Python or Java. Emphasise any projects or roles that demonstrate your ability to design and maintain data pipelines.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your background aligns with the company's mission to help clients become 'AI-Optimal'. Mention specific skills or experiences that relate directly to the job description.
Showcase Technical Skills: Include a section in your application that lists your technical skills, particularly those mentioned in the job description such as SQL, cloud platforms, and data tools like Hadoop or Spark. This will help you stand out as a qualified candidate.
Highlight Collaborative Experience: Since the role involves working within a multi-disciplinary team, be sure to mention any collaborative projects you've been part of. Highlight your ability to work with diverse teams of scientists and engineers to solve complex problems.
How to prepare for a job interview at Placed
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in programming languages like Python, Java, or Scala. Highlight any relevant projects or experiences where you've developed ETL processes or worked with data tools such as Hadoop or Spark.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your ability to troubleshoot and optimise data processing workflows. Prepare examples of how you've approached complex problems in the past, particularly in data integration and management.
✨Understand the Company’s AI Vision
Research the company’s approach to becoming 'AI-Optimal'. Familiarise yourself with their multi-disciplinary methods and be ready to discuss how your background aligns with their goals in leveraging AI and machine intelligence.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, ongoing projects, and the technologies they use. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
