Founding Machine Learning Engineer

Opus Recruitment Solutions; London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

Join a well-funded stealth AI startup as a Machine Learning Engineer, playing a pivotal role in shaping core products. You will be responsible for developing generative voice models, designing high-performance infrastructure, and leading innovative projects in a fast-paced environment.

Qualifications

• PhD or equivalent industry experience required.
• 4+ years of applied research or industry experience preferred.
• Creative problem-solver with passion for building products.

Responsibilities

• Design and implement infrastructure for audio datasets.
• Apply ML techniques to clean and segment speech data.
• Build scalable ML training pipelines using PyTorch.

Skills

Voice conversion

Generative models

Deep learning

Statistical modeling

Problem-solving

Education

PhD in Deep Generative Models, TTS, ASR, NLU

Tools

PyTorch

TensorFlow

Keras

Python

C/C++

PySpark

Kubernetes

Databricks

Apache Arrow

Job description

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Opus Recruitment Solutions provided pay range

This range is provided by Opus Recruitment Solutions. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

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Machine Learning Engineer – Founding Team | Stealth AI Startup (Audio + Generative Models)

Location: London (Hybrid) | Full-time | Competitive Salary + Equity

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 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.

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.
• 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.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology and Research

• Industries

  Software Development and Technology, Information and Media

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