This mid-level data science role is based within a cross-functional delivery team, working on our groundbreaking genAI product. The successful applicant will be crucial in collaboratively researching/modelling/building features to personalise and power intelligent user interactions.
Your responsibilities will include hands-on product development, adherence to industry best practices, including model development and deployment, and the use of techniques such as reinforcement learning to improve product performance.
You will have solid foundations in machine learning theory and practical experience, particularly in NLP, is essential for success. We are also looking to push the performance boundaries of our new product as far as possible, so experience and knowledge of techniques like reinforcement learning would be a bonus.
You will need to be confident in writing production-ready Python code, building end-to-end functionality, and deploying it to a live environment. Experience working within a professional software development setting is essential.
Responsibilities
- Develop, train, and deploy machine learning and AI models, with a focus on NLP and language understanding tasks.
- Write production-grade Python code to build functionality and deploy AI systems to production.
- Work extensively with PyTorch and other machine learning frameworks to build and iterate on models.
- Optimise and productionise models inside the AWS ecosystem, using accelerated hardware resources where needed.
- Build intelligent guardrails to protect our users, product and customers.
- Collaborate closely with cross-functional teams, including other data scientists, product and machine learning engineers, to integrate AI solutions into our tech stack.
- Explore and implement cutting-edge techniques like reinforcement learning and LLM fine-tuning.
- Explore and implement methods to measure product performance and gain insights into performance metrics.
- Documentation and active knowledge sharing.
- Cross-functional team collaboration.
- Adherence to best practices, including code quality and security.
- Continuous learning and development.
- Responding to alerts from monitoring systems on models or technology in the data science domain (during work hours).
Requirements
- Experience in data science and machine learning, with a proven track record of deploying models in production settings.
- Proficiency in writing production-grade Python
- Familiarity with machine learning and deep learning frameworks (e.g. Scikit-learn, PyTorch, TensorFlow).
- Experience with web development frameworks (Django, FastAPI).
- Experience with containerisation technologies (e.g., Docker, ECR) and an understanding of GPU acceleration for deep learning.
- Experience working in a software engineering environment
- Experience with microservice design patterns.
- Experience in a range of machine learning techniques, such as:
- NLP techniques like text embeddings, large language models and entity & intent recognition.
- Reinforcement learning algorithms and applications.
- Recommendation techniques and algorithms.
- Supervised and unsupervised machine learning techniques.
- Prediction and uplift modelling techniques.
- Experience with agentic, RAG, required; council orchestration understanding, beneficial.
- Previous exposure to sales funnel optimisation, sales and marketing insights, sales psychology and its application in data-driven contexts is beneficial.
- Excellent communication skills, with the ability to clearly articulate technical concepts to non-technical stakeholders
Studies have shown that women and people who are disabled, LGBTQ+, neurodiverse or from ethnic minority backgrounds are less likely to apply for jobs unless they meet every single qualification and criteria. We're committed to building a diverse, inclusive, and authentic workplace where everyone can be their best, so if you're excited about this role but your past experience doesn't align perfectly with every requirement on the Job Description, please apply anyway - you may just be the right candidate for this or other roles in our wider team.
Benefits
- Medicash healthcare scheme (reclaim costs for dental, physiotherapy, osteopathy and optical care)
- Life Insurance scheme
- 25 days holiday + bank holidays + your birthday off (rising to 28 after 3 consecutive years with the business & 30 after 5 years)
- Employee Assistance Programme (confidential counselling)
- Gogeta nursery salary sacrifice scheme (save up to 40% per year)
- Enhanced parental leave and pay including 26 weeks’ full maternity pay and 8 weeks’ paternity leave
Salary up to £65,000
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