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- Tasks: Join us to develop a groundbreaking marketing platform using cutting-edge LLM technology.
- Company: Be part of an innovative team reshaping the marketing industry with AI solutions.
- Benefits: Enjoy a hybrid work model with remote flexibility and competitive market rates.
- Why this job: Work on exciting projects that empower users and transform marketing strategies.
- Qualifications: 2+ years in machine learning, advanced Python skills, and experience with LLMs preferred.
- Other info: Contract role with potential for long-term engagement starting January 2025.
The predicted salary is between 48000 - 72000 £ per year.
Machine Learning Engineer – LLM’s:
Type: Contract (Outside IR35)
Hybrid: Remote first approach (1 x per month in the London office)
Rate: Market rate dependant on experience and skills)
Length: 3-6 month rolling (likely to roll for quite some time)
Start Date: Early January 2025.
About the role:
Are you an experienced Machine Learning Engineer passionate about building cutting-edge platforms? We are seeking a talented and innovative individual to join our team in creating a revolutionary solution for the marketing industry. This is an exciting opportunity to work with the latest technologies, including Large Language Models (LLMs), and develop intelligent workflows that empower users.
About the project for Machine Learning Engineer:
You’ll be at the forefront of developing a groundbreaking platform for the marketing world. The platform will leverage LLMs and agent-based systems to deliver intelligent and seamless workflows, reshaping how businesses approach their marketing strategies.
Key Responsibilities for Machine Learning Engineer:
- Develop and optimise APIs and interfaces that enhance user experiences.
- Train, fine-tune, and integrate LLMs into the platform (experience in this is a bonus).
- Design, implement, and optimise algorithms, data structures, and system architectures.
- Build robust testing frameworks to ensure the reliability and scalability of the platform.
- Leverage cloud technologies (GCP/AWS) to ensure efficient and scalable deployment.
- Utilise containerisation tools like Docker for development and deployment workflows.
- Manage code repositories and workflows using Git and GitHub Actions.
- Stay updated with emerging trends and tools in machine learning and AI.
Required Skills and Experience for Machine Learning Engineer:
We are looking for candidates with the following:
- 2+ years of experience as a Machine Learning Engineer or in a related role.
- Knowledge & Exp of LLMs will set you apart for this role (training experience is a strong advantage).
- Proficiency in Python (advanced level).
- Experience with FastAPI or other API frameworks.
- Expertise in designing API interfaces.
- Familiarity with testing frameworks.
- Strong understanding of algorithms, data structures, and optimization.
- Hands-on experience with cloud platforms like GCP or AWS.
- Familiarity with Docker and containerization workflows.
- Proficiency with Git, including automation using GitHub Actions.
Who Should Apply?
We encourage applications from all qualified individuals who are passionate about machine learning and AI innovation. If you have experience as a Machine Learning Engineer and are excited about reshaping the marketing world with advanced technologies, we want to hear from you!
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Machine Learning Engineer - LLM's employer: Evermore Global Sourcing Ltd
Contact Detail:
Evermore Global Sourcing Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - LLM's
✨Tip Number 1
Make sure to showcase your experience with Large Language Models (LLMs) prominently. If you've trained or fine-tuned LLMs, highlight specific projects or outcomes to demonstrate your expertise.
✨Tip Number 2
Familiarize yourself with the latest trends in machine learning and AI, especially those related to marketing. Being able to discuss current innovations during your interview can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your experience with cloud technologies like GCP or AWS. Be ready to explain how you've utilized these platforms in past projects to enhance scalability and efficiency.
✨Tip Number 4
Demonstrate your proficiency in Python and API frameworks like FastAPI by discussing specific challenges you've overcome in previous roles. This will show your problem-solving skills and technical depth.
We think you need these skills to ace Machine Learning Engineer - LLM's
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Machine Learning Engineer, especially any work with Large Language Models (LLMs). Emphasize relevant projects and technologies you've used, such as Python, FastAPI, and cloud platforms like GCP or AWS.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and AI innovation. Discuss how your skills align with the responsibilities of the role, particularly in developing APIs, optimizing algorithms, and leveraging cloud technologies.
Showcase Relevant Projects: If you have worked on projects involving LLMs or similar technologies, be sure to include them in your application. Describe your role, the challenges you faced, and the outcomes of your work to demonstrate your expertise.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops related to machine learning, AI, or cloud technologies. This shows your commitment to staying updated with emerging trends and tools in the field.
How to prepare for a job interview at Evermore Global Sourcing Ltd
✨Showcase Your LLM Experience
Make sure to highlight any experience you have with Large Language Models during the interview. Discuss specific projects where you've trained or fine-tuned LLMs, as this will set you apart from other candidates.
✨Demonstrate Your Technical Skills
Be prepared to discuss your proficiency in Python and any frameworks like FastAPI that you've used. You might be asked to solve a coding problem or explain your approach to designing APIs, so brush up on these skills beforehand.
✨Discuss Cloud Technologies
Since the role involves leveraging cloud platforms like GCP or AWS, be ready to talk about your hands-on experience with these technologies. Share examples of how you've deployed machine learning models in the cloud and the benefits it brought to your projects.
✨Stay Updated on Trends
Show your passion for machine learning by discussing recent trends or tools you've been following. This demonstrates your commitment to continuous learning and innovation, which is crucial for a role focused on cutting-edge technology.
