Machine Learning Engineer – Speech-to-Speech Manchester, UK (Onsite)
Machine Learning Engineer – Speech-to-Speech Manchester, UK (Onsite)

Machine Learning Engineer – Speech-to-Speech Manchester, UK (Onsite)

Manchester Full-Time 48000 - 84000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Build and optimise machine learning models for speech tasks in a groundbreaking project.
  • Company: Join ConnexAI, an award-winning Conversational AI platform transforming productivity with cutting-edge technology.
  • Benefits: Enjoy a collaborative environment, opportunities for growth, and the chance to shape innovative AI solutions.
  • Why this job: Be part of a foundational team influencing product direction and architecture in a fast-paced startup.
  • Qualifications: Strong engineering background with experience in ML systems, particularly in speech technologies and Python.
  • Other info: This is an onsite role based in Manchester, UK, ideal for hands-on tech enthusiasts.

The predicted salary is between 48000 - 84000 £ per year.

Location: Manchester, UK (Onsite)

ConnexAI is developing a transformative product that enables speech-to-speech capabilities in large language models. This is a greenfield project with significant scope to influence both its technical architecture and product impact from the ground up. We’re looking for a hands-on Machine Learning Engineer with deep expertise in building, optimising, and deploying ML systems — particularly in the areas of speech, LLMs, or multimodal learning. You will take cutting-edge research and turn it into production-ready models, enabling real-time, scalable, and reliable multimodal AI experiences.

What You'll Be Doing

  • Building and productising machine learning models for speech-to-text, text-to-speech, and speech-to-speech tasks
  • Translating academic and internal research into scalable, maintainable code and services
  • Developing and maintaining training pipelines, inference services, and deployment workflows
  • Implementing robust data pipelines for sourcing, preprocessing, and versioning multimodal datasets
  • Collaborating with research scientists to refine model architectures and integrate the latest techniques into production
  • Evaluating model performance with custom metrics and developing automated test frameworks for ML systems
  • Contributing to MLOps tooling and infrastructure to support model lifecycle management and monitoring in production
  • Working closely with product, research, and backend engineering to deliver seamless end-to-end features

What We're Looking For

  • Strong engineering background with experience shipping ML systems to production
  • Deep familiarity with speech technologies (ASR, TTS), LLMs, or multimodal machine learning
  • Proficient in Python, with expertise in ML frameworks such as PyTorch
  • Experience building scalable ML pipelines (training, validation, deployment, monitoring)
  • Knowledge of Docker, Kubernetes, and ML deployment platforms
  • Comfort reading and adapting recent research papers into performant implementations
  • Strong debugging and optimisation skills, particularly around model inference speed
  • Experience working in cross-functional teams and contributing to engineering culture and best practices
  • Bonus: experience with streaming audio processing, real-time systems, or speech synthesis engines

Why Join Us?

  • Be part of a foundational team building novel, multimodal AI capabilities
  • Shape the architecture and product direction from an early stage
  • Work in a fast-moving, collaborative environment with a strong focus on execution and innovation
  • Opportunity to grow alongside a rapidly scaling AI startup

About ConnexAI

ConnexAI is an award-winning Conversational AI platform. Designed by a world-class engineering team, ConnexAI's technology enables organizations to maximize profitability, increase revenue and take productivity to new levels. ConnexAI provides cutting-edge, enterprise-grade AI applications including AI Agent, AI Guru, AI Analytics, ASR, AI Voice, and AI Quality.

Machine Learning Engineer – Speech-to-Speech Manchester, UK (Onsite) employer: Connex

ConnexAI is an exceptional employer for Machine Learning Engineers, offering a unique opportunity to work on groundbreaking speech-to-speech technology in the vibrant city of Manchester. With a strong emphasis on innovation and collaboration, employees are encouraged to shape the product's architecture and direction while benefiting from a supportive work culture that prioritises professional growth and development. Join us to be part of a dynamic team where your contributions will directly impact the future of multimodal AI.
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Contact Detail:

Connex Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer – Speech-to-Speech Manchester, UK (Onsite)

Tip Number 1

Familiarise yourself with the latest advancements in speech technologies and multimodal machine learning. Follow relevant research papers and industry news to stay updated, as this knowledge will help you engage in meaningful conversations during interviews.

Tip Number 2

Showcase your hands-on experience by working on personal or open-source projects related to speech-to-speech systems. This practical experience can be a great talking point and demonstrates your ability to apply theoretical knowledge in real-world scenarios.

Tip Number 3

Network with professionals in the field of machine learning and speech technologies. Attend meetups, webinars, or conferences to connect with others and potentially get referrals, which can significantly increase your chances of landing an interview.

Tip Number 4

Prepare for technical interviews by practising coding challenges and system design questions specifically related to ML systems. Focus on areas like model optimisation and deployment, as these are crucial for the role you're applying for.

We think you need these skills to ace Machine Learning Engineer – Speech-to-Speech Manchester, UK (Onsite)

Machine Learning Expertise
Speech Technologies (ASR, TTS)
Large Language Models (LLMs)
Multimodal Machine Learning
Python Programming
Proficiency in ML Frameworks (e.g., PyTorch)
Building Scalable ML Pipelines
Data Pipeline Development
Model Performance Evaluation
Automated Testing for ML Systems
MLOps Tooling and Infrastructure
Docker and Kubernetes Knowledge
Debugging and Optimisation Skills
Cross-Functional Team Collaboration
Adaptability to Research Developments

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience with machine learning systems, particularly in speech technologies and LLMs. Use specific examples of projects you've worked on that relate to the job description.

Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your skills align with their needs, especially your experience in building and deploying ML systems and your familiarity with relevant technologies.

Showcase Relevant Projects: If you have any personal or professional projects related to speech-to-speech capabilities or multimodal learning, be sure to mention them. Include links to your GitHub or portfolio to demonstrate your hands-on experience.

Highlight Collaboration Skills: Since the role involves working closely with cross-functional teams, emphasise your ability to collaborate effectively. Provide examples of how you've contributed to team projects and fostered a positive engineering culture.

How to prepare for a job interview at Connex

Showcase Your Technical Skills

Be prepared to discuss your experience with machine learning frameworks, particularly PyTorch. Highlight specific projects where you've built or optimised ML systems, especially in speech technologies or LLMs.

Demonstrate Problem-Solving Abilities

Expect technical questions that assess your debugging and optimisation skills. Prepare to explain how you've tackled challenges in model inference speed or data pipeline issues in past projects.

Familiarise Yourself with Recent Research

Since the role involves translating academic research into practical applications, review recent papers related to speech-to-speech technologies. Be ready to discuss how you would implement these findings in a production environment.

Emphasise Collaboration Experience

ConnexAI values teamwork, so share examples of how you've worked in cross-functional teams. Discuss your contributions to engineering culture and best practices, and how you’ve collaborated with product and research teams.

Machine Learning Engineer – Speech-to-Speech Manchester, UK (Onsite)
Connex
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  • Machine Learning Engineer – Speech-to-Speech Manchester, UK (Onsite)

    Manchester
    Full-Time
    48000 - 84000 £ / year (est.)

    Application deadline: 2027-07-15

  • C

    Connex

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