In 2023, we extended our models from purely using CNNs in the cloud to innovating with ensemble models that combine the best of CNNs, ViTs, and OpenClip models to improve the accuracy and the value of our models in real world use. We’ve also developed mobile SDKs that run on Android and on iOS which include models that provide fault tolerant guidance to end users of apps that use our SDKs. All of these models need someone willing and able to monitor their performance and behaviours so we can make ongoing improvements to the models and the SDKs.
You’ll be working with the rest of the ML team, led by Sumanas Sarma, the mobile team, and the full stack developers on an ongoing basis.
Key Duties and Responsibilities
- Deploying models and training pipelines on GCP (VertexAI, Cloud Functions, Cloud Run)
- Developing, enhancing, and performance tuning ML models that run on Android and iOS smartphones and tablet devices. These may include end-user’s devices and dedicated equipment.
- Devising adaptive predictive models that combine edge and cloud computing to suit the current operational environments where connectivity may be sporadic across devices with a wide range of performance characteristics.
- Considering the holistic aspects of establishing performant, useful, and trustworthy ML including all aspects of labelling, testing, validation, guides, as well as devising learning and calibration. This may include collaborating with domain experts, professional labellers, etc. With the current size of the team, data engineering will be a vital aspect.
- Mentoring and guiding junior and mid-level team members in best practices
- Making recommendations for improving our engineering processes
- Helping to establish conventions & incorporate industry-oriented good-practices when building, training, deploying & monitoring machine learning pipelines in production
Qualifications and Requirements
- 3+ years of experience in software engineering, with a focus on cloud native development & deployment in Python
- Demonstrable expertise and capabilities in the effective use of Computer Vision or other aspects of modern Machine Learning
- Experience with deep learning frameworks such as Tensorflow, PyTorch, JAX.
- Strong understanding of engineering principles and best practices
- Experience deploying and managing workloads on GCP or equivalent cloud platforms
- Ability to mentor and guide junior and mid-level team members
- Experience deploying & maintaining services in production
- Flexible hours & remote working
- Mentorship from world class engineering leads (see company advisors)
- International, diverse team
- Unlimited Coursera subscription
- Competitive salaries
- 6 month salary reviews
- Pension scheme
- 30 days holiday (including public and bank holidays)
- Screening Interview
- Focused Technical Interview