At a Glance
- Tasks: Design and develop evaluation pipelines for cutting-edge audio models in speech generation and recognition.
- Company: Join Cantina Labs, a pioneering social AI company transforming storytelling and connection.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on innovation and collaboration.
- Why this job: Be a founding member of the evaluation team and shape the future of AI technology.
- Qualifications: Strong experience in model evaluation, user studies, and programming skills required.
The predicted salary is between 60000 - 80000 € per year.
About Cantina
Cantina Labs is a social AI company, developing a suite of advanced real‑time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social‑AI platform, is just the beginning.
About the Role
We are seeking an experienced Machine Learning Engineer to focus on audio model evaluation, specifically for speech generation and recognition models. This role involves designing and developing comprehensive model evaluation pipelines for both development and production environments, as well as creating automated dashboards for reporting evaluation results. As the founding member of our evaluation team, you will lead our evaluation efforts and shape the future growth of the evaluation team.
What You’ll Do
- Design model evaluation pipelines for models in development and production.
- Design user studies for subjective model evaluations.
- Convert requirements into measurable metrics.
- Develop automated evaluation dashboards to visualize model performance and compare results.
- Train new models to capture new and different evaluation metrics.
- Communicate with the model team to help design better models based on evaluation results.
- Communicate with the data team to determine the type of data necessary to improve model performance.
- Communicate with the product manager to ensure product requirements are correctly measured.
- Help grow the evaluation team as the founding member.
- Lead the evaluation team in the future.
What You’ll Bring
- Strong experience and intuition for designing metrics that capture model performance.
- Strong experience designing user studies on Mechanical Turk or similar platforms.
- Experience with model training and fine‑tuning for model evaluation.
- Strong statistical knowledge and experience in statistically comparing evaluation results and making decisions.
- Very strong engineering and programming skills.
- Experience training ASR and TTS models.
- Experience at ML teams working on large‑scale machine learning problems (e.g., >3B parameters with >1M hours of data).
Machine Learning Enginer, Core Evaluations in London employer: Cantina Labs
Cantina Labs is an exceptional employer, offering a dynamic work environment where innovation thrives and creativity is encouraged. As a Machine Learning Engineer, you will not only lead the evaluation team but also have access to cutting-edge technology and resources that foster professional growth. With a strong emphasis on collaboration and a culture that values diverse perspectives, Cantina Labs provides a unique opportunity to shape the future of social AI in a supportive and forward-thinking setting.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Enginer, Core Evaluations in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Cantina Labs. Use LinkedIn or even Twitter to connect and engage with them. A friendly message can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work on model evaluation pipelines or any relevant projects. This is your chance to demonstrate your expertise in audio models and metrics, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with ASR and TTS models, and how you’ve designed user studies. Practice common interview questions and have examples ready to share.
✨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 take that extra step to connect directly with us.
We think you need these skills to ace Machine Learning Enginer, Core Evaluations in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with model evaluation, user studies, and any relevant projects that showcase your skills in designing metrics and pipelines.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're passionate about AI and how your background aligns with our mission at Cantina Labs. Share specific examples of your work in audio model evaluation or similar areas to grab our attention.
Showcase Your Technical Skills:Don’t forget to highlight your engineering and programming skills! Mention any relevant languages or tools you’ve used, especially those related to machine learning and model training, as these are crucial for the role.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role without any hiccups!
How to prepare for a job interview at Cantina Labs
✨Know Your Models Inside Out
Make sure you have a solid understanding of the audio models you'll be working with, especially in terms of speech generation and recognition. Brush up on the latest advancements in ASR and TTS models, as well as any relevant metrics for evaluating their performance.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Be ready to explain how you would design model evaluation pipelines and user studies. Practise articulating your thought process clearly, as this will showcase your engineering skills and problem-solving abilities.
✨Showcase Your Statistical Knowledge
Since strong statistical knowledge is crucial for this role, prepare to discuss how you've used statistics to compare evaluation results in past projects. Bring examples of how you've made data-driven decisions based on your evaluations to demonstrate your expertise.
✨Communicate Effectively
As a founding member of the evaluation team, communication will be key. Be prepared to discuss how you would collaborate with model teams, data teams, and product managers. Highlight any past experiences where effective communication led to successful project outcomes.
