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For Companies At a Glance
- Tasks: Design and deploy cutting-edge machine learning models and systems.
- Company: Join a pioneering company revolutionizing AI with innovative ML technologies.
- Benefits: Enjoy remote work flexibility and the chance to work with top-tier tech.
- Why this job: Be part of a mission-driven team making a real impact in AI applications.
- Qualifications: 5+ years in machine learning, expertise in LLMs, and strong Python skills required.
- Other info: Work with VC-backed start-ups and cutting-edge technology in a collaborative environment.
The predicted salary is between 48000 - 72000 £ per year.
Job Description
Snr ML Engineer – Machine Learning, LLMs, MLOps, RAG, Prompt Engineering, UK Remote
My client is revolutionizing the way businesses are leveraging AI with cutting edge Machine Learning technologies. Recently funded and looking for Snr ML Engineers to join the mission to innovate and make an impact.
What You’ll Do
As a Senior Machine Learning Engineer, you will:
- Design, build, and deploy scalable machine learning models and systems.
- Work extensively with Large Models (LLMs) to develop innovative AI-driven applications.
- Implement and optimize Retrieval-Augmented (RAG) architectures to enhance model performance.
- Lead MLOps initiatives to streamline the development, deployment, and monitoring of ML workflows.
- Apply Prompt Engineering techniques to fine-tune LLM outputs and improve usability.
- Collaborate with cross-functional teams to integrate AI solutions into real-world applications.
- Leverage Google Cloud Platform (GCP) to build and deploy cloud- ML solutions.
- Utilize Python and key ML libraries (Pandas, PyTorch, Numpy, etc.) for model development.
What We’re Looking For
- 5+ years of experience in machine learning, with a strong focus on building production-grade models.
- Expertise in LLMs, including engineering, fine tuning, model evaluation, deployment, and real-world applications.
- Hands-on experience with MLOps tools and pipelines (e.g., MLflow, Kubeflow, or similar).
- Solid programming skills in Python, with experience in ML libraries such as Numpy, PyTorch, or Pandas.
- Knowledge of Retrieval-Augmented (RAG) techniques, embeddings, knowledge graphs.
- Strong experience working with Google Cloud Platform (GCP) for ML workflows.
- Data Science/ Computational Linguistics: Building evaluation frameworks and datasets, model iteration, gap analysis.
To apply please send your CV to
WMTech
WMTech is trusted by leaders in the Cyber Security, AI and Enterprise Software sectors to advise on talent strategy specifically for Start-Ups. Our clients are heavily VC backed, unicorn status, pre-IPO start-ups with pioneering technology.
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Snr ML Engineer - Machine Learning, LLMs, MLOps, RAG, Prompt Engineering, UK Remote employer: ZipRecruiter
Contact Detail:
ZipRecruiter Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Snr ML Engineer - Machine Learning, LLMs, MLOps, RAG, Prompt Engineering, UK Remote
✨Tip Number 1
Make sure to showcase your hands-on experience with Large Language Models (LLMs) in your discussions. Highlight specific projects where you've engineered, fine-tuned, or deployed LLMs, as this will resonate well with the hiring team.
✨Tip Number 2
Familiarize yourself with the latest MLOps tools and pipelines like MLflow or Kubeflow. Being able to discuss how you've implemented these tools in past projects can set you apart from other candidates.
✨Tip Number 3
Since the role emphasizes collaboration with cross-functional teams, prepare examples of how you've successfully worked with different departments to integrate AI solutions. This will demonstrate your ability to communicate and work effectively in a team setting.
✨Tip Number 4
Brush up on your knowledge of Google Cloud Platform (GCP) and be ready to discuss how you've utilized it for machine learning workflows. Specific examples of cloud-based projects will show your practical experience and readiness for the role.
We think you need these skills to ace Snr ML Engineer - Machine Learning, LLMs, MLOps, RAG, Prompt Engineering, UK Remote
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning, especially with LLMs and MLOps. Include specific projects where you've designed, built, or deployed scalable ML models.
Showcase Relevant Skills: Emphasize your programming skills in Python and familiarity with key ML libraries like Pandas, PyTorch, and Numpy. Mention any hands-on experience with Google Cloud Platform (GCP) and MLOps tools.
Highlight Achievements: Include quantifiable achievements in your application. For example, describe how your work improved model performance or streamlined ML workflows, particularly using Retrieval-Augmented techniques.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for AI and machine learning. Discuss why you want to join this innovative company and how your background aligns with their mission.
How to prepare for a job interview at ZipRecruiter
✨Showcase Your Experience with LLMs
Be prepared to discuss your hands-on experience with Large Language Models. Highlight specific projects where you've engineered, fine-tuned, or deployed LLMs, and be ready to explain the impact of your work.
✨Demonstrate MLOps Knowledge
Since MLOps is a key part of the role, make sure to talk about your experience with MLOps tools like MLflow or Kubeflow. Discuss how you've streamlined ML workflows in previous roles and any challenges you overcame.
✨Familiarize Yourself with RAG Techniques
Understand Retrieval-Augmented Generation techniques and be ready to discuss how you've implemented them in past projects. Prepare examples that illustrate how these techniques improved model performance.
✨Highlight Your Cloud Experience
As the role involves leveraging Google Cloud Platform, be ready to share your experience with GCP. Discuss specific services you've used for deploying ML solutions and any relevant projects that showcase your cloud skills.
