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- Tasks: Lead a team in developing and deploying cutting-edge machine learning models.
- Company: Join a dynamic team revolutionizing AI technology in a collaborative environment.
- Benefits: Enjoy a competitive salary, unlimited holiday, and a Deliveroo budget.
- Why this job: Make a real impact in AI while growing your leadership skills and technical expertise.
- Qualifications: Extensive software engineering experience and proven track record in machine learning applications required.
- Other info: Hybrid work model with 3 days in London; ideal for innovative thinkers.
The predicted salary is between 56000 - 68000 £ per year.
Lead Machine Learning Engineer (LLM engineering & deployment)
Salary range: £70,000 – £85,000, hybrid (London 3 days a week)
Are you as passionate about good software engineering as you are about LLMs? Want to make a significant impact and contribute to the company’s success? Do you want to lead a team operating at the very cutting edge of AI technology, whilst remaining hands-on and delivering your own solutions? If yes, then read on …
About the Role
As the Lead Machine Learning Engineer, you will be involved in everything to do with the development and deployment of enterprise-grade machine learning models into production. Splitting your time between supporting and leading a team of 2-3 Machine Learning Engineers whilst delivering your own production models and inputting significantly into architectural discussions. You will work closely with data engineers, analysts and software developers to breathe life into our suite of products.
This is a role for an experienced technical Lead, who can combine hands-on work with team management.
Responsibilities
Leadership:
- Lead a team of 2-3 data scientists, fostering a collaborative and innovative environment.
- Provide technical guidance, motivation, and mentorship to team members, promoting their professional growth.
- Define and prioritize project goals and objectives, ensuring the team’s alignment with company objectives.
Delivery:
- Lead the development of machine learning-based applications, from ideation to deployment.
- Apply your expertise in Natural Language Processing (NLP) to solve complex problems and enhance AI tools.
- Collaborate with software engineers and data engineers to integrate machine learning models into production systems.
- Review performance of production models, performing evaluation and tuning
Must-have requirements
- Extensive professional experience as a Software Engineer
- Commercial experience in fine-tuning foundation LLMs
- Some experience leading a small team of Machine Learning or Software Engineers
- Proven track record of delivering machine learning-based applications commercially into production (not academia or research)
- Engineering mindset with experience working on cloud platforms (ideally, AWS although Azure and GCP are also fine)
- Expertise in Python programming
Preferred, non-essential requirements:
- Experience working with AWS Sagemaker pipelines
- Experience with Langchain, Retrieval Augmented Generation (RAG) or Vector Databases
Benefits
- £70,000 – 85,000 base salary (salary assessment will be primarily based on experience)
- Deliveroo weekly budget
- AXA healthcare
- Unlimited holiday
About the Team
Our team is a multi-disciplinary team of experts with everyone contributing their own area of specialism; from infrastructure to knowledge graphs, Real Estate Operations to dialogue design.
Working in a truly collaborative style, where everyone is heard and brings something valuable to the conversation allows us to push the boundaries in this new technology area. We are fundamentally challenging the way one of the largest industries in the world operates, and our commercial success pays testament to the skill, commitment and passion that our team displays every day.
Apply now and help us shape the future of AI
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Lead Machine Learning Engineer (LLM engineering & deployment) employer: Story Terrace Inc.
Contact Detail:
Story Terrace Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Machine Learning Engineer (LLM engineering & deployment)
✨Tip Number 1
Make sure to showcase your leadership skills during the interview. Prepare examples of how you've successfully led a team in the past, especially in machine learning projects. Highlight your ability to foster collaboration and innovation within your team.
✨Tip Number 2
Demonstrate your hands-on experience with LLMs by discussing specific projects where you fine-tuned foundation models. Be ready to explain the challenges you faced and how you overcame them, as this will show your problem-solving skills.
✨Tip Number 3
Familiarize yourself with the latest trends in Natural Language Processing (NLP) and be prepared to discuss how they can be applied to enhance AI tools. This knowledge will set you apart as a candidate who is not only experienced but also forward-thinking.
✨Tip Number 4
Since the role involves collaboration with software and data engineers, brush up on your communication skills. Practice explaining complex technical concepts in simple terms, as this will demonstrate your ability to work effectively in a multi-disciplinary team.
We think you need these skills to ace Lead Machine Learning Engineer (LLM engineering & deployment)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your extensive experience as a Software Engineer and your commercial experience in fine-tuning foundation LLMs. Emphasize any leadership roles you've held, especially in managing small teams of Machine Learning or Software Engineers.
Craft a Compelling Cover Letter: In your cover letter, express your passion for software engineering and LLMs. Discuss how your hands-on experience and leadership skills align with the responsibilities of the Lead Machine Learning Engineer role. Mention specific projects where you successfully delivered machine learning applications into production.
Showcase Relevant Skills: Highlight your expertise in Python programming and any experience you have with cloud platforms like AWS, Azure, or GCP. If you have worked with AWS Sagemaker pipelines or technologies like Langchain or Vector Databases, be sure to include that as well.
Prepare for Technical Questions: Be ready to discuss your technical knowledge and experience during the interview process. Prepare to explain your approach to developing and deploying machine learning models, as well as how you would lead a team in a collaborative environment.
How to prepare for a job interview at Story Terrace Inc.
✨Show Your Passion for LLMs
Make sure to express your enthusiasm for large language models during the interview. Share specific examples of projects you've worked on that involved LLMs, and discuss how they align with the company's goals.
✨Demonstrate Leadership Skills
Since this role involves leading a small team, be prepared to discuss your leadership style. Share experiences where you motivated and guided team members, and how you fostered a collaborative environment.
✨Highlight Your Technical Expertise
Be ready to dive deep into your technical skills, especially in Python and cloud platforms like AWS. Discuss any relevant experience you have with fine-tuning LLMs and deploying machine learning applications.
✨Prepare for Architectural Discussions
As the role involves significant input into architectural discussions, familiarize yourself with the company's tech stack and be prepared to share your thoughts on best practices for integrating machine learning models into production systems.
