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For Companies At a Glance
- Tasks: Join a pioneering team to develop cutting-edge audio and generative models.
- Company: Be part of a well-funded stealth AI startup with top-tier investors.
- Benefits: Enjoy a competitive salary, equity options, and a hybrid work environment.
- Why this job: Shape innovative products and make a real impact in the AI space.
- Qualifications: PhD or equivalent experience in relevant fields; strong ML framework skills required.
- Other info: Ideal for builders and creative problem-solvers eager to lead in a fast-paced setting.
The predicted salary is between 43200 - 72000 £ per year.
A well-funded, early-stage startup backed by top-tier investors is seeking an ambitious Machine Learning Engineer to join as their first full-time ML hire. As a core member of the founding team, you’ll generate voice and speech-to-speech models and your work will directly shape the company’s core products and have a real impact on users. The ideal candidate is a builder at heart—someone who’s either been a founder or has shipped impressive side projects—and is excited to work in a fast-paced, high-performance environment.
What You’ll Do
- Design and implement cost-efficient, high-performance infrastructure for storing and transforming massive audio datasets.
- Apply ML audio and DSP techniques to clean, segment, and filter speech data.
- Manage large-scale cloud data storage with a deep understanding of cost-performance tradeoffs.
- Build scalable ML training pipelines in PyTorch using large datasets.
- Contribute to research and development of generative voice and speech-to-speech models.
- Prototype and implement novel ML/statistical approaches to enhance product capabilities.
- Develop robust testing pipelines to evaluate model performance on audio data.
What We’re Looking For
- PhD in a relevant field (e.g., Deep Generative Models, TTS, ASR, NLU), or equivalent industry experience.
- Deep expertise in voice conversion, generative models, deep learning, or statistical modeling.
- Strong hands-on experience with ML frameworks (PyTorch, TensorFlow, Keras).
- Proficiency in Python and C/C++.
- Experience with scalable data tools (e.g., PySpark, Kubernetes, Databricks, Apache Arrow).
- Proven ability to manage GPU-intensive data processing jobs.
- 4+ years of applied research or industry experience.
- Creative problem-solver with a bias for action and a passion for building world-class products.
Bonus Points
- Extensive experience in applied research, especially in voice conversion, speech synthesis, or NLP.
- PhD specialization in voice or speech-related ML fields.
- A track record of thought leadership through publications, open-source contributions, or patents.
Founding Machine Learning Engineer employer: JR United Kingdom
Contact Detail:
JR United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Machine Learning Engineer
✨Tip Number 1
Network with professionals in the AI and machine learning community, especially those who have experience in audio processing or generative models. Attend relevant meetups, webinars, or conferences to make connections that could lead to referrals.
✨Tip Number 2
Showcase your hands-on experience by working on personal projects related to voice conversion or speech synthesis. Having a portfolio of projects can demonstrate your skills and passion for the field, making you stand out as a candidate.
✨Tip Number 3
Engage with the startup's online presence. Follow them on social media, participate in discussions, and share insights related to their work. This shows your genuine interest in the company and can help you get noticed by the hiring team.
✨Tip Number 4
Prepare to discuss your problem-solving approach during interviews. Be ready to share specific examples of how you've tackled challenges in previous projects, particularly those involving machine learning and audio data.
We think you need these skills to ace Founding Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with audio and generative models. Emphasise any projects or roles that showcase your skills in Python, PyTorch, and deep learning.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also expresses your passion for building innovative products. Mention specific projects you've worked on that relate to the job description, especially those involving voice conversion or speech synthesis.
Showcase Your Projects: If you have side projects or contributions to open-source related to machine learning or audio processing, include them in your application. This demonstrates your hands-on experience and enthusiasm for the field.
Highlight Your Problem-Solving Skills: In your application, provide examples of how you've tackled complex problems in previous roles. Focus on your creative solutions and the impact they had on your projects or teams.
How to prepare for a job interview at JR United Kingdom
✨Showcase Your Projects
Be prepared to discuss any impressive side projects or previous work that demonstrates your skills in machine learning and audio processing. Highlight specific challenges you faced and how you overcame them.
✨Understand the Company’s Vision
Research the startup's mission and products thoroughly. Be ready to articulate how your expertise aligns with their goals, especially in generative voice and speech-to-speech models.
✨Demonstrate Technical Proficiency
Brush up on your knowledge of ML frameworks like PyTorch and TensorFlow. Be ready to answer technical questions and possibly solve problems on the spot to showcase your hands-on experience.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s technology stack, team dynamics, and future projects. This shows your genuine interest and helps you assess if the startup is the right fit for you.
