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For Companies At a Glance
- Tasks: Advance AI assistants to tackle complex technical questions and enhance system performance.
- Company: Innovative AI company focused on making technical knowledge accessible.
- Benefits: Fully remote role, competitive salary, and opportunities for professional growth.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: Master's or PhD in relevant fields and strong ML/NLP expertise.
- Other info: Dynamic, fast-paced environment with a focus on learning and innovation.
The predicted salary is between 36000 - 60000 £ per year.
About Us
We build AI assistants that make technical knowledge instantly accessible. As a research engineer, you will work on advancing our system’s ability to answer increasingly complex technical questions. Our technology is already deployed on real-world developer documentation, where users can query information directly through an integrated AI assistant.
The Challenges You’ll Work On
- Evaluating a retrieval-augmented-generation (RAG) system in production without labelled data
- Designing your own benchmarks from scratch
- Building an agentic retrieval pipeline that adapts between fast and more thorough query strategies
- Fine-tuning embeddings or reranking models
What You’ll Do
- Collaborate closely with the core team and software engineers
- Stay up-to-date with the latest research and apply new ideas to real product challenges
- Design, run and analyse experiments to push system performance
You Might Be a Great Fit If You Have
- A Master's or PhD in Computer Science, Machine Learning, Mathematics, Statistics, or a related field
- Strong knowledge of machine learning, deep learning (including LLMs), and natural language processing
- Hands-on experience training, fine-tuning, and deploying LLMs
- Experience working with vector databases, search indices, or data stores for retrieval use cases
- Significant experience building evaluation systems for search or language models
- Familiarity with information retrieval techniques (e.g., lexical search, dense vector search)
- Comfort working in a fast-moving environment with ambiguous problem spaces
- A desire to learn more about ML research
Please note that this position is fully remote in Europe but you MUST have the right to work in your country of residence.
Machine Learning Engineer | Python | Pytorch | Natural Language Processing | LLM | Large Langua[...] in Bury employer: Enigma
Contact Detail:
Enigma Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer | Python | Pytorch | Natural Language Processing | LLM | Large Langua[...] in Bury
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or attend virtual meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, Pytorch, and NLP. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and problem-solving techniques. Practice coding challenges related to LLMs and retrieval systems to demonstrate your expertise during technical interviews.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Machine Learning Engineer | Python | Pytorch | Natural Language Processing | LLM | Large Langua[...] in Bury
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, Pytorch, and NLP. We want to see how your skills align with the challenges we face, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about working with AI assistants and how your background in machine learning can help us tackle complex technical questions.
Showcase Your Projects: If you've worked on any cool projects involving LLMs or retrieval systems, make sure to mention them! We love seeing practical applications of your skills, so include links or descriptions of your work.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Enigma
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of Python, Pytorch, and natural language processing. Be ready to discuss your hands-on experience with LLMs and how you've applied them in real-world scenarios. This will show that you're not just familiar with the concepts but can also implement them effectively.
✨Prepare for Technical Challenges
Expect to tackle some technical questions or challenges during the interview. Practice explaining your thought process when designing benchmarks or evaluating retrieval systems. Being able to articulate your approach to problem-solving will impress the interviewers.
✨Show Your Collaborative Spirit
Since the role involves working closely with a core team, be prepared to discuss your past experiences collaborating with software engineers or researchers. Highlight any projects where teamwork led to successful outcomes, as this will demonstrate your ability to thrive in a collaborative environment.
✨Stay Updated on ML Trends
Keep yourself informed about the latest research and advancements in machine learning and NLP. Mention any recent papers or technologies that excite you during the interview. This shows your passion for the field and your commitment to continuous learning, which is crucial for this role.
