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- Tasks: Join a start-up to develop and deploy large language models, focusing on training and optimization.
- Company: Exciting US-based start-up expanding into the UK with a focus on AI and machine learning.
- 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 degree in relevant fields and expertise in MLOps and Python programming required.
- Other info: Work in a dedicated GPU cluster and stay updated with the latest advancements in AI.
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.
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ML Engineer employer: SitePoint Pty.
Contact Detail:
SitePoint Pty. 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 machine learning and NLP. Follow relevant research papers, attend webinars, and engage with the community on platforms like GitHub or LinkedIn to stay updated and showcase your knowledge during interviews.
✨Tip Number 2
Build a portfolio that highlights your experience with large language models. Include projects where you've implemented MLOps best practices, such as CI/CD pipelines and containerization, to demonstrate your practical skills and understanding of the field.
✨Tip Number 3
Network with professionals in the AI and machine learning space. Attend meetups, conferences, or online events to connect with potential colleagues and learn more about the company culture at the start-up you're interested in.
✨Tip Number 4
Prepare for technical interviews by practicing coding challenges and system design questions related to machine learning. Use platforms like LeetCode or HackerRank to sharpen your skills and be ready to tackle real-world problems during the interview process.
We think you need these skills to ace ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in machine learning, especially with large language models. Emphasize your expertise in MLOps practices and any projects that showcase your programming skills in Python.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with their focus on NLP and machine learning, and mention specific projects or experiences that demonstrate your problem-solving abilities.
Showcase Relevant Projects: If you have worked on projects involving TensorFlow, PyTorch, or similar frameworks, be sure to include these in your application. Provide links to your GitHub or any other portfolio where they can see your work.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops you've completed related to machine learning or AI. This shows your commitment to staying updated with advancements in the field, which is crucial for this role.
How to prepare for a job interview at SitePoint Pty.
✨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've implemented MLOps best practices, as this will demonstrate your expertise in the field.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your analytical skills and problem-solving approach. Prepare examples of how you've transformed complex theoretical research into practical applications, especially in the context of natural language processing.
✨Discuss Collaboration Experience
Since the role involves close collaboration with research teams, be ready to share experiences where you worked in a team setting. Emphasize your ability to build and maintain data sets and scalable training pipelines, showcasing your teamwork and communication skills.
✨Stay Updated on Industry Trends
Research recent advancements in machine learning, NLP, and AI before the interview. Being able to discuss these trends and their relevance to the company's projects will show your passion for the field and your commitment to continuous learning.
