<sup>We are looking for a Senior Research Scientist to join our world-class team and lead cutting-edge work on large language model (LLM) post-training. This is not just about applying standard fine-tuning techniques - it's about building the future of dialogue systems with novel approaches to reasoning, reinforcement learning, audio-first LLMs, and more.

As a Senior Research Scientist at PolyAI, you’ll lead impactful research projects from ideation through to deployment. You’ll be driving innovation in how we train and adapt LLMs for real-world conversations - spanning voice, text, and multimodal contexts. You'll work on frontier techniques such as:</sup>

• ^{Conversational reinforcement learning}

• ^{Streaming and continuous turn-taking}

• ^{Audio-native LLMs}

• ^{Distillation of reasoning models}

• ^Long-context

• ^{Efficient adaptation}

^{You’ll also play a key role in shaping the scientific direction of our research, mentoring junior colleagues, and collaborating cross-functionally to bring research into production.}

^{Responsibilities:}

• ^{Lead and execute complex research projects with clear business impact.}

• ^{Design and implement novel post-training strategies including preference tuning, reward modeling, and synthetic supervision.}

• ^{Develop innovative model architectures and training approaches for conversational AI, including speech-aware and multimodal models.}

• ^{Conduct empirical studies to assess model performance in live deployments and iterate quickly based on real-world data.}

• ^{Generate, collect, and annotate training data - including synthetic and real-world conversational datasets - with an eye for quality and bias mitigation.}

• ^{Design robust evaluation metrics and benchmarks for LLM-based assistants in customer service domains.}

• ^{Work closely with engineering and product teams to integrate research into production environments.}

• ^{Collaborate with legal and compliance teams to ensure responsible use of data and models.}

^{Stay current with academic and industry advances in LLMs, ASR, TTS, RLHF, and multimodal learning.}

^{Requirements:}

• ^{PhD in Machine Learning, Natural Language Processing, Computer Science, or a related field.}

• ^{5+ years of hands-on experience in deep learning.}

• ^{Proven track record of research innovation, including published work or deployed systems.}

• ^{Strong programming skills in Python and deep learning frameworks like PyTorch.}

• ^{Demonstrated expertise in at least one domain area such as reinforcement learning, conversational AI, audio modelling, or LLM alignment.}

• ^{Experience leading projects end-to-end, from ideation to deployment.}

• ^{Excellent communication skills with the ability to write clear technical documents and explain complex concepts to diverse audiences.}

• ^{Comfortable working in ambiguity and driving clarity through experimentation and data.}

^{Preferred Qualifications:}

• ^{Experience with speech technologies such as ASR and TTS.}

• ^{Familiarity with cloud environments (AWS, GCP, Azure).}

• ^{Exposure to RLHF, reward modelling, or human preference data collection.}

• ^{Prior work on real-time systems, streaming inference, or memory-efficient model deployment.}
  
  

^{We offer competitive compensation based on experience, expertise, and the level of responsibility. This role also includes equity, giving you the opportunity to share in the long-term success of the business.}

^{The listed expectations reflect what we're hiring for, so we encourage you to review the job description carefully.}

<sup>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</sup>