Find a job 
Featured Companies 
Featured Universities 
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 thrive in a fast-paced setting.
The predicted salary is between 36000 - 60000 £ 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 work on generative voice and speech-to-speech models, and your work will directly shape the company’s core products and have a real impact on users.
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 involved in startups. Attend relevant meetups or conferences where you can connect with potential colleagues or mentors who might provide insights into the company culture and expectations.
✨Tip Number 2
Showcase your passion for building and innovation by sharing your side projects or contributions to open-source initiatives. This demonstrates your hands-on experience and commitment to the field, which is crucial for a founding team member.
✨Tip Number 3
Familiarise yourself with the latest trends and advancements in generative models and audio processing. Being well-versed in current research will not only prepare you for interviews but also show your enthusiasm for the role and the industry.
✨Tip Number 4
Prepare to discuss your problem-solving approach and past experiences in detail. Be ready to share specific examples of how you've tackled challenges in machine learning projects, particularly those involving audio data or generative models.
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 in audio and generative models. Emphasise any projects or roles that demonstrate your ability to design and implement ML infrastructure.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for building innovative products and your experience in fast-paced environments. Mention specific projects that align with the job description, especially those involving voice conversion or deep learning.
Showcase Your Projects: If you have side projects or contributions to open-source related to machine learning, make sure to include them. Highlight any work that demonstrates your skills in Python, PyTorch, or other relevant technologies.
Prepare for Technical Questions: Be ready to discuss your technical expertise in detail. Prepare to explain your approach to building scalable ML training pipelines and managing large datasets, as well as any challenges you've faced in previous roles.
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, especially in audio and generative models. Highlight specific challenges you faced and how you overcame them.
✨Understand the Company’s Vision
Research the startup's mission and values. Be ready to articulate how your background and expertise align with their goals, particularly in shaping core products that impact users.
✨Demonstrate Technical Proficiency
Brush up on your knowledge of ML frameworks like PyTorch and TensorFlow, as well as your programming skills in Python and C/C++. Be ready to answer technical questions or even solve problems on the spot.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving abilities. Think about how you would approach designing scalable ML training pipelines or managing large datasets, and be ready to discuss your thought process.
