Senior Machine Learning Engineer

PolyAI; London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading company in conversational AI is seeking a senior Machine Learning Engineer specializing in speech recognition. In this role, you will focus on Automatic Speech Recognition and Text to Speech, developing strategies for data generation and model evaluation. You will collaborate with various teams to enhance technologies and ensure compliance, while enjoying a flexible working environment and numerous benefits.

Benefits

Employee share options plan

25 days holiday plus bank holidays

Flexible working from home policy

Work from outside the UK for up to 6 months

Enhanced parental leave

Bike2Work scheme

Annual learning and development allowance

One-off WFH allowance

Company-funded fertility and family-forming programmes

Private healthcare and dental cover

Qualifications

• 3+ years of experience with deep learning and statistical models.
• Strong knowledge of data quality standards and annotation processes.

Responsibilities

• Train models and conduct experiments to assess model performance.
• Generate, collect, and annotate contact center data.
• Develop strategies for domain-specific tasks.

Skills

Deep Learning

Statistical Models

Python

Communication

Education

Degree in Computer Science

Tools

PyTorch

AWS

GCP

Azure

Job description

PolyAI automates customer service through lifelike voice assistants that let customers lead a conversation. Our voice assistants make it possible for businesses to deliver outstanding customer service that rivals their human agents. Our customers, which include the world's leading logos, are expanding how they use our platform, driving automation of critical customer service operations and integrating PolyAI into their daily customer service workflows.

As a senior Machine Learning Engineer specialising in speech recognition, you will play a key role in shaping and implementing strategies for (synthetic or not) data generation, collection, and annotation, as well as evaluating and experimenting with various models and novel architectures. Your primary focus will be on Automatic Speech Recognition (ASR), Text to Speech (TTS), and AudioLLMs (LLMs that take audio as input).

Responsibilities:

• Train models and conduct experiments to assess model performance in live deployments
• Generate, collect, and annotate contact center data from sources such as real customer calls, chats, online open datasets, and synthetic data.
• Develop strategies to achieve state of the art performance on domain-specific tasks: improving perceived latency, turn taking behaviour, accuracy of specific data points extraction (addresses, phone numbers, postcodes etc).
• Develop robust evaluation benchmarks to track improvements in production models
• Stay informed about the latest advancements in machine learning, ASR, TTS, and LLM to continuously enhance our technologies
• Build tooling which allows cooperation between clients/users of the machine learning models and MLEs (data pipelines, automated evaluation, training and deployment routine, AB testing frameworks etc).
• Collaborate with the legal and compliance team to address any compliance or data privacy-related issues
• Work closely with product and engineering teams to ensure alignment with business and production goals

Requirements:

• A degree in Computer Science, Machine Learning, or a related field, or equivalent industry experience
• 3+ years of experience working with deep learning and statistical models
• Strong knowledge of data quality standards and annotation processes, with the ability to independently evaluate and improve models
• Proficiency in Python and familiarity with relevant ML frameworks and libraries (e.g., PyTorch)
• Experience with cloud services such as AWS, GCP, or Azure
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to diverse audiences
• A passion for solving technical challenges and driving practical solutions

Preferred Qualifications:

• Experience working with LLMs and data preparation pipelines.
• Experience with speech models, such as ASR or TTS.

(UK) Benefits

Participation in the company's employee share options plan

25 days holiday, plus bank holidays

Flexible working from home policy

Work from outside of the UK for up to 6 months each year

Enhanced parental leave

Bike2Work scheme

Annual learning and development allowance

One-off WFH allowance when you join

Company-funded fertility and family-forming programmes

Menopause care programme with Maven

Private healthcare and dental cover, discounts on gym members and relaxation apps, and access to a range of mental health programs

At PolyAI, we take great pride in our values-they guide everything we do. We believe that a strong culture leads to meaningful work and lasting impact.

Our core values are:

• Only the best: We expect the best from our people, we hire people that expect the best from themselves, and we nurture this drive for excellence.
• Ownership: We care deeply about what we do. We take ownership of our initiatives, decisions and outcomes.
• Relentlessly improve: We demand more from ourselves and are always evolving. Continuous, obsessive improvement is the only way we will transform the world of conversational AI.
• Bias for action: Our world moves quickly and so do we. We take calculated risks and we deliver impact fast.
• Disagree and commit: We are all working toward the same goal. If we don't agree with something, we work hard to understand it and when a decision is made, we accept it and give it our all.
• Build for people: We are hyper-focused on delivering the best automated experiences possible so that we can empower people to get exactly what they need, when they need it.

PolyAI is proud to be an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All employment decisions at PolyAI will be based on the business needs without attention to ethnicity, religion, sexual orientation, gender identity, family or parental status, national origin, neurodiversity status or disability status.

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