
Senior ML Research Engineer
- London
- Permanent
- Full-time
- Designs tests and experiments to build machine-learning models for detecting and recognising food and non-food items from images and videos and optionally texts, not excluding other contextual data like date, time, season, geography etc to improve the performance of the models
- Maintains a high level of data quality via directing and guiding the annotation team and third-parties in data annotation and labelling
- Manages the data efficiently for model training and evaluation
- Applies state-of-the-art model architectures and techniques to improve the models
- Prepares reports and presents results to summarise main findings and conclusions
- Presents results of scientific research to stakeholders and conferences, and publishes articles outlining the methodology and results of research undertaken
- Writes software and algorithms in training and running the models within Winnow applications.
- Collaborate with other teams at Winnow in deploying the models to Winnow's applications to embedded systems like NVIDIA Jetson devices and to the cloud like AWS and GCP
- Minimum Master's degree in Machine Learning, Computer Science, Mathematics, Statistics or equivalent. Ideally PhD level of above with commercial experience.
- Experience in developing and deploying ML models end-to-end gained in at least one corporate environment
- Expertise in at least one of: Bayesian Learning, Reinforcement Learning, Object Detection, Image Classification, Action Recognition, Image Generation, Semantics Segmentation. Signal Processing and NLP are an additional bonuses.
- Expertise in working with TensorFlow or PyTorch.
- Expertise in adopting state-of-the-art model architectures and customising them to support new business requirements.
- Experience working with Linux and AWS.
- Experience running model inference technologies like ONNX, TensorRT, Ollama and vLLM.
- Good programming skills using Python.
- Working independently, prototyping and finding solutions that can be productionised.
- Teamwork, knowledge transfer, process documentation.
- Passionate about Machine Learning and Artificial Intelligence.
- Languages: Node.js, Java, AngularJS, Python, C++, Rust
- Android apps
- REST APIs
- Designing and manufacturing IoT 'smart' edge devices and expanding using Linux powered devices on the field collecting data using cutting edge technologies
- Focus on security, user authentication, permissions, data integrity
- AWS Cloud using EC2, Redshift, Sagemaker, S3 and other services
- Agile team using Scrum or Kanban using the Atlassian stack (JIRA, Confluence, BitBucket)
- Reporting and Analytics using Postgres, Jupyter, Airflow and Grafana
- Model inference on edge devices via ONNX and TensorRT
- Model training using TensorFLow and PyTorch
- Competitive base salary
- Company stock options package
- Matching pension scheme
- 2 Wellness hours per month plus a £48 gross monthly wellness allowance
- 25 days of paid vacation time in addition to national holidays, plus the option to buy a further 5 days annual leave
- Company part-funded private health insurance and eyecare allowance
- Life insurance (3 times base salary)
- Employee Assistance Programme - 24/7 helpline for your wellbeing
- Learning and development allowance of £300 annually
- Cycle to work scheme
- Hybrid way of working - we're all in the office on Tuesdays and Thursdays
- Company provided breakfast & snacks on office days
- Early Finish Fridays - log off at 3 PM on a Friday if you have completed your tasks by then
- Great office space in central London and a great working environment
- You will love what you do - waking up every day solving one of the biggest social problems of our generation - food waste
- Committed team members with broad experience who share a common passion to build a world class business