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- Tasks: Design and develop scalable data platforms for processing massive training data.
- Company: Join a stealth-mode AI lab with a team of top-tier engineers and investors.
- Benefits: Enjoy a competitive salary, equity, relocation support, and 28 days holiday.
- Why this job: Work on cutting-edge AI research and tackle complex challenges in a dynamic environment.
- Qualifications: Proficiency in Python, back-end engineering, and understanding of core CS fundamentals required.
- Other info: Ideal for those passionate about data and eager to contribute to open-source projects.
The predicted salary is between 48000 - 84000 £ per year.
We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Microsoft, Bloomberg and Goldman Sachs. We are backed by prominent investors from the US and the UK, including institutional VC funds and C-level executives of global technology companies.
Responsibilities:
- Design and develop a highly-scalable data platform capable of ingesting and processing hundreds of terabytes of training data.
- Design and develop methodologies and metrics to better understand the underlying quality, structure and distribution of training data.
- Architect training data validation, integrity and safety mechanisms for state-of-the-art ML models.
Requirements:
- Experience in back-end engineering developing data platforms or large-scale extract-transform-load (ETL) pipelines.
- Proficiency in Python for data pipelines, distributed systems and micro-services.
- Familiarity with AWS, GCP or Azure, an understanding of containerisation (e.g., Docker) and infrastructure-as-code software.
- Excellent understanding of core CS fundamentals, including common abstract data structures and algorithms with the ability to apply them to optimise production systems.
- Contributions to and experience in open-source projects.
- Experience with TypeScript and front-end libraries such as React or Next.js.
If you are passionate about data and enjoy solving complex challenges, we would love to hear from you.
Benefits:
- Competitive salary, equity and benefits package.
- Financial assistance for relocation to London.
- 28 days + public holidays allowance.
- Opportunities for professional growth and progression with your career.
Graduate Software Engineer - Machine Learning employer: Zettafleet
Contact Detail:
Zettafleet Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Software Engineer - Machine Learning
✨Tip Number 1
Familiarise yourself with the latest trends and advancements in machine learning. Follow relevant blogs, attend webinars, and participate in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with the open-source community by contributing to projects related to machine learning or data engineering. This hands-on experience will enhance your skills and provide you with practical examples to discuss during your interview, showcasing your commitment to continuous learning.
✨Tip Number 3
Network with professionals in the AI and machine learning space. Attend meetups, conferences, or workshops where you can connect with industry experts. Building these relationships can lead to valuable insights and potential referrals for job opportunities.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges that focus on algorithms and data structures. Use platforms like LeetCode or HackerRank to sharpen your problem-solving skills, as these are crucial for the role of a Graduate Software Engineer in Machine Learning.
We think you need these skills to ace Graduate Software Engineer - Machine Learning
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, data platforms, and programming languages like Python. Emphasise any projects or roles that demonstrate your skills in back-end engineering and ETL pipelines.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and problem-solving. Mention specific experiences that align with the job description, such as contributions to open-source projects or familiarity with cloud services like AWS or GCP.
Showcase Technical Skills: Include a section in your application that lists your technical skills, particularly those mentioned in the job description, such as containerisation (Docker), infrastructure-as-code, and knowledge of algorithms and data structures.
Highlight Team Collaboration: Since the role involves working in a team, mention any previous experiences where you collaborated on projects, especially in fast-paced environments. This will show your ability to work effectively within a team of skilled professionals.
How to prepare for a job interview at Zettafleet
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, data platforms, and ETL pipelines. Bring examples of projects you've worked on that demonstrate your proficiency in these areas, as well as your understanding of algorithms and data structures.
✨Demonstrate Your Passion for Machine Learning
Express your enthusiasm for machine learning and AI. Share any contributions you've made to open-source projects or relevant research you've conducted. This will show your commitment to the field and your eagerness to learn.
✨Understand the Company’s Vision
Research the company’s background and its stealth-mode AI laboratory focus. Familiarise yourself with their goals and the technologies they use, such as AWS, GCP, or Azure, to align your answers with their mission during the interview.
✨Prepare Questions for the Interviewers
Have thoughtful questions ready to ask your interviewers about the team dynamics, the challenges they face in developing machine learning models, and opportunities for professional growth. This shows your interest in the role and helps you assess if it's the right fit for you.
