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- Tasks: Lead the enhancement of AI language models and establish safety measures for client LLMs.
- Company: Join an innovative AI company at the forefront of technology and research.
- Benefits: Enjoy a full-time role with opportunities for growth and collaboration in a dynamic environment.
- Why this job: Be part of groundbreaking AI research that shapes the future and impacts society positively.
- Qualifications: Mid-senior level experience in AI or related fields is essential.
- Other info: Connect with Thomas Moraldo for more insights about this exciting opportunity.
The predicted salary is between 48000 - 72000 £ per year.
As a Lead Research Engineer at this innovative AI company, your role will involve enhancing and refining language models to function as evaluators, while also leveraging your expertise to establish safety measures for client LLMs, advancing the field to new heights.
Key responsibilities will include:
- Directing LLMs to become highly effective evaluators that align with human preferences through cutting-edge post-training methods.
- Curating and generating large, high-quality datasets to improve our evaluator, ensuring its effectiveness in assessing cutting-edge and future AI models.
- Designing comprehensive evaluation frameworks, encompassing tools, datasets, and metrics for thorough analysis of alignment and safety risks.
- Contributing to the development of AI safety research, sharing significant insights at leading conferences within the industry.
- Playing a vital role in the growth of our applied research division, setting a high standard for excellence that drives the organization forward.
Please get in touch with Thomas Moraldo to find out more.
Lead Research Engineer employer: Seer
Contact Detail:
Seer Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Research Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in language models and AI safety. Being well-versed in current trends and technologies will not only boost your confidence but also demonstrate your passion for the field during discussions.
✨Tip Number 2
Network with professionals in the AI community, especially those who have experience in LLMs and AI safety. Attend relevant conferences or webinars where you can meet industry leaders and potentially get insights that could help you stand out.
✨Tip Number 3
Prepare to discuss your previous projects related to dataset curation and evaluation frameworks. Be ready to share specific examples of how your work has contributed to improving AI models, as this will showcase your hands-on experience.
✨Tip Number 4
Reach out to Thomas Moraldo directly to express your interest and ask insightful questions about the role. This proactive approach can leave a positive impression and may give you an edge over other candidates.
We think you need these skills to ace Lead Research Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Lead Research Engineer. Familiarise yourself with language models, evaluation frameworks, and AI safety research to tailor your application effectively.
Highlight Relevant Experience: In your CV and cover letter, emphasise your experience with language models, dataset curation, and AI safety measures. Use specific examples that demonstrate your ability to lead projects and contribute to research advancements.
Craft a Compelling Cover Letter: Your cover letter should not only express your enthusiasm for the role but also outline how your skills align with the company's goals. Mention any relevant conferences you've attended or papers you've published in the field.
Proofread Your Application: Before submitting, carefully proofread your application materials. Ensure there are no typos or grammatical errors, as attention to detail is crucial in a technical role like this one.
How to prepare for a job interview at Seer
✨Showcase Your Technical Expertise
As a Lead Research Engineer, you'll need to demonstrate your deep understanding of language models and AI safety. Be prepared to discuss your previous projects, the methodologies you used, and how they relate to the responsibilities outlined in the job description.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about how you would enhance LLMs as evaluators or design evaluation frameworks. Practising these scenarios can help you articulate your thought process clearly during the interview.
✨Highlight Your Collaborative Skills
This role involves working closely with other teams. Be ready to share examples of how you've successfully collaborated on research projects or cross-functional teams in the past. Emphasise your ability to communicate complex ideas effectively to diverse audiences.
✨Stay Updated on Industry Trends
Familiarise yourself with the latest advancements in AI and language models. Being knowledgeable about current trends and challenges in AI safety will not only impress your interviewers but also show your passion for the field and commitment to continuous learning.
