About the Role
As the Machine Learning Lead and one of our first employees, you’ll be key to helping us create the world's leading multilingual conversational AI platform. By joining us early in our journey, we hope you’ll be limitless, truly creative and innovative when working with our team to decide how we build the platform. Your primary responsibility will be to keep our ML framework state-of-the-art, by adapting the latest deep learning / natural language processing technologies from the academic and open-source community.
Qualities/Attitude
- Understanding that ‘perfect is the enemy of good’.
- Equally a thinker and doer.
- Excited about being part of a rapid growth journey and accepting innate uncertainty and constant change.
- Good organisational skills (including time and task management, and working efficiently as part of a team).
- Works in a straight-forward, collaborative and inclusive way and is non-political.
Responsibilities
- Build and expand on existing NLP algorithms.
- Transform data science prototypes and apply appropriate ML algorithms and tools.
- Design machine learning systems.
- Develop robust ETL pipelines and automated processes for ingesting and processing data.
- Manage available resources such as hardware, data, and personnel so that deadlines are met.
- Maintain, debug and improve our ML infrastructure.
- Increase automation, simplify and improve the ML pipelines.
- Work closely with the technical CEO to plan, implement, release and maintain new features and functionality in our technology platform.
- Debug reported issues with the production system (customer or internal), and work on solutions in a timely manner.
Qualifications / Skills
- Masters degree or (ideally) PhD in a technical discipline (e.g., computer science, physics, maths) or 3+ years of similar research experience.
- 3+ years in the search/AI-related field.
- 5+ years of Python experience.
- 2+ years of experience in deep learning frameworks (e.g., Tensorflow, Pytorch, MXNet, PaddlePaddle).
- Able to implement the latest DL model using existing APIs and open-source libraries in a short time.
- Extensive knowledge of ML frameworks, libraries, data structures, data modelling, and software architecture.
- Familiarity with the agile software development process, CI/CD workflow, ticket management, code review, version control, etc.
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like sci-kit-learn), Linux and Cloud (AWS).
- Good understanding of the mainstream deep learning models from multiple domains: computer vision, NLP, reinforcement learning, model optimization, etc.
Nice to Have
- Relevant publications in high-impact journals.
- Contributed to open-source projects.
- Experience with Multilingual Language Models.
- Kubernetes.
- Knowledge of data pipelining (e.g., via Airflow) and prior experience with cloud-based ML model deployment.
- Jina.ai, Haystack and any relevant Semantic Search technologies.
Benefits
- Stock options between 0.5% and 3%.
- Salary between £60k and £100k.
- Visa sponsorship if necessary.
- Hybrid working (a mix of in-office and work-from-home).
- Generous remote work (3 months per year).
- Beautiful office space in Canary Wharf, London.
- Team retreats.
- Flex holiday (can exchange bank holidays for more convenient days).
- Modern equipment, MacBook Pro / PC.
- Bi-Annual Salary Reviews.