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- Tasks: Join our GenAI team to build and optimize NLP projects with large language models.
- Company: We're a leading financial services company expanding our innovative AI capabilities.
- Benefits: Competitive salary up to 95k, bonus potential, and hybrid work model (3 days in office).
- Why this job: Be part of cutting-edge AI projects that drive real business impact and enhance your tech skills.
- Qualifications: 3+ years in Data Science or ML Engineering, 2+ years with LLMs, strong Python skills required.
- Other info: No sponsorship available; apply now to shape the future of AI in finance!
The predicted salary is between 68000 - 112000 £ per year.
AI Engineer
Up to 95k + Bonus
Location: London – 3 days a week in office
My client is a leading financial services company who is in the process of growing their GenAI team. They are looking for an AI Engineer who will be an individual technical contributor to help build their NLP projects focusing on large language models. This role includes working the full life cycle from proof of concept to fine-tuning and deployment.
Responsibilities:
- Identify where GenAI can be used to support the business and deliver measurable advantages.
- Collaborate with the Data Science and AI team to implement scalable AI applications.
- Improve and optimize the infrastructure by enhancing MLOps capabilities, CI/CD pipelines, user interfaces, and AI Python libraries.
- Develop effective prompts for AI models while fine-tuning them.
- Conduct thorough evaluations of third-party GenAI and LLM technologies.
- Take ownership of projects from initial research and development stages all the way through production deployment.
- Write production-ready code.
What You Need to Succeed:
- Minimum of 3 years working as a Data Scientist or Machine Learning Engineer on machine learning projects.
- At least 2 years experience using LLMs.
- Strong background in Python.
- Exposure to MLOps including CI/CD, Docker, Kubernetes.
- Familiarity with software best practices.
- Experience working with non-technical stakeholders.
- Confident using AWS.
- Bonus if you have used Kafka, Databricks, and RAG.
Unfortunately, sponsorship is not provided for this role.
If you are interested, please apply here or reach out to .
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Senior GenAI Engineer employer: Xcede Recruitment Solutions
Contact Detail:
Xcede Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior GenAI Engineer
✨Tip Number 1
Make sure to showcase your experience with large language models (LLMs) in your conversations. Highlight specific projects where you've successfully implemented LLMs, as this will demonstrate your hands-on expertise.
✨Tip Number 2
Familiarize yourself with the latest trends in GenAI and NLP. Being able to discuss recent advancements or technologies during your interview can set you apart and show your passion for the field.
✨Tip Number 3
Prepare to discuss your experience with MLOps, CI/CD, and cloud platforms like AWS. Be ready to provide examples of how you've optimized infrastructure or improved deployment processes in past roles.
✨Tip Number 4
Since collaboration is key in this role, think of examples where you've worked with non-technical stakeholders. Being able to communicate complex AI concepts in an understandable way will be a big plus.
We think you need these skills to ace Senior GenAI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Data Scientist or Machine Learning Engineer, especially focusing on your work with large language models (LLMs) and any relevant projects you've completed. Use keywords from the job description to align your skills with what the company is looking for.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss specific examples of how you've contributed to AI projects, particularly in NLP and MLOps. Mention your experience with Python and any tools like Docker or Kubernetes that are relevant to the position.
Showcase Your Technical Skills: Be prepared to discuss your technical skills in detail. Highlight your experience with AWS, CI/CD pipelines, and any other technologies mentioned in the job description. If you have experience with Kafka, Databricks, or RAG, make sure to include that as well.
Prepare for Interviews: If selected for an interview, be ready to discuss your previous projects and how you approached challenges in AI development. Prepare to explain your thought process when fine-tuning models and optimizing infrastructure. Familiarize yourself with the company's use of GenAI and be ready to suggest how you can contribute.
How to prepare for a job interview at Xcede Recruitment Solutions
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with large language models and how you've applied them in previous projects. Highlight specific examples where you contributed to the full life cycle of a project, from proof of concept to deployment.
✨Demonstrate Collaboration Skills
Since this role involves working closely with Data Science and AI teams, be ready to share experiences where you successfully collaborated with non-technical stakeholders. Emphasize your ability to communicate complex technical concepts in an understandable way.
✨Discuss MLOps Experience
Make sure to talk about your familiarity with MLOps practices, including CI/CD, Docker, and Kubernetes. Provide examples of how you've optimized infrastructure or improved workflows in past roles.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving skills, especially related to AI applications. Think of scenarios where you identified opportunities for GenAI to deliver business advantages and how you approached those challenges.
