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).
Basic qualifications
- 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
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
Tags & focus areas
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