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- Tasks: Build and deploy cutting-edge AI systems using large language models.
- Company: Join a pioneering generative AI company at the forefront of NLP and ML innovation.
- Benefits: Enjoy flexible work options and the chance to work on impactful projects.
- Why this job: Be part of a team solving real enterprise problems with AI technology.
- Qualifications: 5+ years in software engineering or ML development with deep Python expertise required.
- Other info: Bonus points for experience with RAG systems or agentic workflows.
The predicted salary is between 54000 - 84000 £ per year.
Seer are currently partnered with a generative AI company who are searching for 'Senior Research Engineers' with strong software engineering experience to help build and scale cutting-edge LLM-based applications. This role is ideal for someone who’s passionate about applying AI to solve real enterprise problems and wants to work at the forefront of NLP and ML innovation.
What can you expect to be doing?
- Build and deploy production-grade AI systems using large language models
- Design scalable retrieval and agentic architectures
- Collaborate with engineers and researchers to develop new AI features
- Evaluate model performance and drive continuous improvements
- Translate business needs into high-impact AI solutions
- Implement strong testing and MLOps practices
What will you bring?
- 5+ years in software engineering or ML development
- Deep Python expertise and experience building production systems
- Strong knowledge of ML techniques, tooling (e.g. MLflow, W&B), and cloud deployment
- Experience with LLMs and frameworks like LangChain, Hugging Face, or LlamaIndex
- Bonus: hands-on work with RAG systems or agentic workflows
If this is of interest, please apply immediately!
Senior Research Engineer employer: Seer
Contact Detail:
Seer Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Research Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in large language models (LLMs) and their applications. Being able to discuss recent developments or breakthroughs in this area during your interview can demonstrate your passion and knowledge.
✨Tip Number 2
Showcase your experience with MLOps practices by preparing examples of how you've implemented testing and deployment strategies in previous projects. This will highlight your ability to build production-grade AI systems effectively.
✨Tip Number 3
Network with professionals in the AI and ML community, especially those who work with LLMs. Engaging in discussions or attending relevant meetups can provide insights and potentially lead to referrals for the position.
✨Tip Number 4
Prepare to discuss how you translate business needs into AI solutions. Think of specific examples where your technical skills have directly contributed to solving real enterprise problems, as this aligns closely with what the role requires.
We think you need these skills to ace Senior Research Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your software engineering experience and any relevant projects involving large language models (LLMs). Emphasise your deep Python expertise and any specific ML techniques or tools you've used.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how it can solve real enterprise problems. Mention specific experiences that demonstrate your ability to build and deploy production-grade AI systems and collaborate effectively with teams.
Showcase Relevant Projects: If you have worked on projects involving LLMs, retrieval architectures, or MLOps practices, be sure to include these in your application. Provide details about your role, the technologies used, and the impact of your work.
Highlight Continuous Learning: Mention any ongoing education or certifications related to machine learning, NLP, or software engineering. This shows your commitment to staying at the forefront of innovation in the field.
How to prepare for a job interview at Seer
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and any relevant ML frameworks. Highlight specific projects where you've built production systems, especially those involving large language models.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your ability to translate business needs into AI solutions. Prepare examples of how you've tackled real enterprise problems using AI in previous roles.
✨Familiarise Yourself with MLOps Practices
Since the role involves implementing strong testing and MLOps practices, brush up on your knowledge of tools like MLflow and W&B. Be ready to discuss how you ensure model performance and continuous improvement.
✨Collaborative Mindset
This position requires collaboration with engineers and researchers. Think of examples where you've successfully worked in a team to develop new features or improve existing systems, and be ready to share those experiences.
