Golang / Go Job: Machine Learning Engineer

Machine Learning Engineer at Senseye

🇬🇧 United Kingdom › Anywhere, Headquartered In Southampton, UK   (Posted Sep 14 2017)

About the company
Senseye, the Uptime as a Service product is a cloud-based tool to help manufacturers avoid downtime and save money by automatically forecasting machine failure without the need for expert manual analysis. It’s a revolution in predictive maintenance that can be used on any machine from any manufacturer, taking information from existing Industrial IoT sensors and platforms to automatically diagnose existing failures and provide warning of others months in advance.

Job position
Permanent - Remote work possible

Job description
Senseye is an exciting and rapidly expanding start up in the field of condition monitoring and prognostics. We are developing a cutting edge cloud product to provide scalable prognostics and advanced condition monitoring to the manufacturing sector. Our team of engineers consist of software engineers, data scientists, UI experts, physicists and mechanical engineers. Following successful investment funding and strong traction from large multi-national clients, we are looking to expand the engineering team.
We are seeking an ambitious and versatile machine learning engineer, whose responsibility will be to understand research generated by our researchers and put this into production software. You will work closely with the wider development and R&D teams to bring research into production.

Our Stack:
- Predominantly Golang backend, with some Node, Java, R and Python
- Mongo, Redis, Neo4j and InfluxDB data storage
- Microservice architecture
- AWS
- Docker + ECS orchestration

Benefits:
- Work where you want, when you want
- Super flexible leave
- Startup vibe - autonomy, trust and excellence
- Dedicated time to give back to the open source community

Salary will be in the region of £30,000 to £60,000, depending on experience

Sound fun? Come on and have a chat with us…

Skills & requirements
BSc/MSc in Computer Science/Engineering (or other numerical discipline). Relevant PhD preferred.
Experience in machine learning, including supervised and unsupervised techniques
Experience building complex applications with modern best practices (e.g. test driven development, continuous deployment, code reviews)
Familiar with the building blocks of scalable cloud systems: Linux, containers and service oriented architecture
Thrive working on the bleeding edge and can learn new technologies independently
Comfortable in a culture of fast iteration
Attracted to complex problems
Experience working as part of a team on a rapidly growing application and codebase is ideal

Apply now!