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- Tasks: Join a start-up to develop and deploy cutting-edge large language models.
- Company: Exciting US-based start-up expanding into the UK with a focus on AI innovation.
- Benefits: Enjoy competitive salary, stock options, health benefits, and access to top-tier compute resources.
- Why this job: Make a real impact in AI while collaborating with top talent in a supportive environment.
- Qualifications: Master's in Computer Science or related field; expertise in MLOps and Python required.
- Other info: Work in a dynamic team focused on making technology accessible and eco-friendly.
The predicted salary is between 43200 - 72000 £ per year.
Hays Software Engineering are looking for a Machine Learning Engineer to join a heavily backed, exciting Large Language Model start-up based in the US, looking to build their presence in the UK starting with an engineering hub in London. What you will be doing: Conduct research and implement solutions for the development, training, and deployment of large language models, with a focus on both pre-training and post-training processes, including fine-tuning, alignment, and optimisation. Collaborate closely with research teams to build, optimise, and maintain data sets, as well as scalable training and data pipelines for LLMs, ensuring efficient deployment in production environments. Build and maintain comprehensive documentation for infrastructure components and systems. Design and implement systems that ensure reproducibility and traceability in data preparation. Develop and maintain detailed documentation and codebases to ensure reproducibility and best practices in research and development workflows. Stay updated with advancements in machine learning, NLP, and AI, and evaluate their relevance to ongoing and future projects. What we are looking for: Master's degree in Computer Science, Machine Learning, Mathematics, or a related field, with a strong emphasis on natural language processing or machine learning. Expertise in MLOps best practices, including model versioning, CI/CD pipelines, containerisation, and cloud deployment for large-scale models. Proficient programming skills in Python, with familiarity in machine learning frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools like MLflow and Kubeflow. Exceptional analytical and problem-solving abilities, with a knack for transforming complex theoretical research into practical applications. What you will get in return: Supportive Environment: Benefit from huge funding, collaborating with top-tier talent. Top-Tier Compute: Access a dedicated GPU cluster for research. Impactful Work: Shape the future of AI applications, making technology more accessible and eco-friendly. Competitive Benefits: Enjoy a competitive salary, stock options, health benefits, and more.Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at (url removed)
ML Engineer employer: Hays Technology
Contact Detail:
Hays Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer
✨Tip Number 1
Familiarize yourself with the latest advancements in large language models and natural language processing. This will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with the machine learning community through forums, webinars, or local meetups. Networking can lead to valuable connections and insights that may give you an edge in the application process.
✨Tip Number 3
Showcase any personal projects or contributions to open-source initiatives related to MLOps or NLP. This practical experience can set you apart from other candidates and highlight your hands-on skills.
✨Tip Number 4
Prepare to discuss specific challenges you've faced in previous projects and how you overcame them. This will demonstrate your problem-solving abilities and analytical thinking, which are crucial for a Machine Learning Engineer.
We think you need these skills to ace ML Engineer
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Machine Learning Engineer position. Understand the key responsibilities and required skills, especially focusing on MLOps best practices and programming languages like Python.
Tailor Your CV: Customize your CV to highlight relevant experience in machine learning, natural language processing, and any projects involving large language models. Emphasize your expertise in tools like TensorFlow, PyTorch, and MLOps frameworks.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and machine learning. Mention specific projects or experiences that align with the company's goals and how you can contribute to their mission of making technology more accessible.
Showcase Your Knowledge: In your application, demonstrate your understanding of current trends in machine learning and NLP. Mention any recent advancements or research that excite you and how they could be relevant to the role.
How to prepare for a job interview at Hays Technology
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills in Python and your experience with machine learning frameworks like TensorFlow and PyTorch. Highlight specific projects where you implemented MLOps best practices, as this will demonstrate your hands-on expertise.
✨Discuss Your Research Experience
Since the role involves conducting research for large language models, be ready to talk about any relevant research you've done. Explain how you approached problem-solving and the impact of your work on previous projects.
✨Emphasize Collaboration
This position requires close collaboration with research teams. Share examples of how you've successfully worked in teams, particularly in cross-functional settings, and how you contributed to building and maintaining data sets or training pipelines.
✨Stay Updated on Industry Trends
Demonstrate your passion for machine learning and NLP by discussing recent advancements in the field. Be prepared to evaluate their relevance to the company's projects, showing that you're proactive about staying informed and continuously learning.
