At a Glance
- Tasks: Build advanced search technologies and improve search quality with innovative models.
- Company: Join Perplexity, a cutting-edge tech company in London.
- Benefits: Gain hands-on experience, mentorship, and work in a dynamic environment.
- Other info: 12-24 week full-time internship with excellent growth opportunities.
- Why this job: Make a real impact on how users discover information through advanced ML.
- Qualifications: Strong foundation in machine learning, Python skills, and a passion for learning.
The predicted salary is between 20000 - 30000 € per year.
Requirements
- Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems.
- Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects.
- Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required.
- Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required.
- Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment.
- Experience with Rust will be a plus.
What the job involves
- Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking.
- You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information.
- Internship program: 12 - 24 weeks, full-time, in-person in the London office.
- Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers.
- Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models.
- Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks.
- Support deployment and monitoring of search and ranking models in a scalable and performant way.
- Help build and iterate on RAG pipelines for grounding and answer generation.
- Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML.
Search Machine Learning Engineer Intern employer: Deepstreamtech
Perplexity is an exceptional employer for aspiring machine learning engineers, offering a dynamic internship experience in the heart of London. With a strong emphasis on collaboration and mentorship, interns will have the opportunity to work alongside seasoned professionals, contributing to cutting-edge search technologies while honing their skills in a supportive and innovative environment. The company fosters a culture of curiosity and ownership, providing ample opportunities for personal and professional growth in the fast-evolving field of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Search Machine Learning Engineer Intern
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insights that might just land you that internship.
✨Tip Number 2
Show off your projects! Whether it's a personal project or something from your coursework, make sure to have a portfolio ready. Highlight any machine learning models you've built or worked on, especially if they relate to search or recommendation systems.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and ML frameworks like PyTorch or TensorFlow. Practice coding challenges and be ready to discuss your thought process when solving problems.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Search Machine Learning Engineer Intern
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your strong foundation in machine learning and any relevant projects you've worked on. We want to see your experience with Python and ML frameworks like PyTorch or TensorFlow, so don’t hold back!
Tailor Your Application:Customise your application to reflect the job description. Mention any coursework or projects related to information retrieval, ranking, or recommender systems. This shows us you’re a great fit for the role!
Be Yourself:We love self-driven and curious candidates! Share your passion for learning and how you take ownership of your projects. A bit of personality goes a long way in making your application stand out.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our team.
How to prepare for a job interview at Deepstreamtech
✨Brush Up on Your ML Basics
Make sure you have a solid understanding of machine learning concepts, especially those related to information retrieval and ranking. Review your coursework or projects and be ready to discuss how they relate to the role.
✨Show Off Your Python Skills
Since experience with Python and ML frameworks is key, prepare to talk about your projects using PyTorch, TensorFlow, or JAX. Bring examples of your code or projects that demonstrate your skills and problem-solving abilities.
✨Familiarise Yourself with Evaluation Metrics
Even if you haven't worked with A/B testing before, it’s good to understand how model quality is evaluated. Brush up on offline metrics and be prepared to discuss how you would approach evaluating models in a practical setting.
✨Demonstrate Your Curiosity and Ownership
This role requires a self-driven attitude, so think of examples where you've taken initiative in your projects or studies. Be ready to share how you tackle challenges and what you do to keep learning in a fast-paced environment.
