Applied Research Engineer (Machine Learning / Ops)
Intenseye is an AI-powered Workplace Safety platform that helps the world’s largest enterprises to scale employee health and safety across their facility footprints globally to significantly reduce workplace accidents and fatalities.
Every 7 seconds a worker is injured on the job. The human and economic cost of workplace injuries around the world is a staggering $250 billion per year. At Intenseye, we believe that the health and safety of workers is non-negotiable.
Using the latest breakthroughs in cutting edge artificial intelligence, machine learning, deep learning and computer vision, Intenseye empowers health and safety teams to monitor their facilities, provide complete visibility for the first time ever, and operationalize their rapid response procedures and start their Journey to Zero.
Connecting to existing cameras within facilities, Intenseye empowers EHS leaders to see the unseen hazards and save lives proactively, through 24/7 analysis of workplaces and real-time leading indicator data.
Join Intenseye on the Journey to Zero!
We are seeking our first dedicated Machine Learning Engineer for the growing Engineering team based in Istanbul.
As a member of the AI Infrastructure team at Intenseye, you will be responsible for building systems to accelerate the development and deployment of machine learning models built by our Research team. Our models span the range from computer vision and deep learning and are trained on massive datasets to deliver improvements to our customers.
Intenseye is using AI to solve major Health & Safety issues for our customers. We have a proven product and market fit and are already closing enterprise customers.
Now is an incredibly exciting time to join our growing Engineering team!
- Work with our Machine Learning research to automate aspects of our pipeline and deploy research models in production.
- Build elastic data pipelines that process billions of events per day.
- Build highly available and observable model inference services.
- Work with our ML research to automate aspects of our pipeline and deploy research models in production.
- Work with our Infrastructure team to build core abstractions and create standards and best practices for building systems.
- Be a self-starter who can own projects end-to-end, from requirements, scoping, design, to implementation.
- Have attention to detail and a good sense for automation, debugging, and troubleshooting.
Sound like you?
- Positive attitude with a strong desire to learn!
- Solid background in algorithms, data structures, and object-oriented programming.
- Experience in building scalable and fault-tolerant distributed systems that process large volumes of data.
- Experience working with a cloud technology stack (eg. AWS or GCP).
- Experience building, deploying, and monitoring complex microservice architectures.
- Experience with machine learning frameworks and libraries (PyTorch, Tensorflow, Kubeflow, Seldon).
- Experience with Python, Docker, Kubernetes, and Infrastructure as code (e.g. terraform).
- Degree in computer science or related field.
- Previous startup experience would be great but not essential
What we offer?
- Great Salary, Health Benefits and Equity in a fast-growing business
- Experience working with a fast development and research team of engineers using the latest and greatest technologies
- Flexibility on work location and hours (Ideally to be based from our Istanbul office, but we are open to remote working with occasional trips to our office for meetings)
- Play a key role in growth of the company
- Saving lives and changing the industry with AI-powered health and safety!
Our Tech Stack
- - Scala, Go, Python for programming language.
- - Google Cloud Platform (GCP) and Amazon Web Services (AWS) for cloud services.
- - Docker, Kubernetes for orchestration tools.
- - Apache Pulsar for message queueing.
- - Prometheus, Grafana for monitoring.
- - Elasticsearch for analytics
- - Redis for distributed caching.
- - Linkerd for service mesh.
- - Buildkite for CI/CD.
- - PostgreSQL for RDBMS.
- - Git for version control.
- - Replicated for on-premise.
Our interview process
- Zoom chat with our Head of People (45 mins)
- Take-Home Task (x7 days to complete)
- Zoom interview with x2 Engineers to review task / technical deep dive (90 mins)
- Zoom interview (or On-site) with CTO & Lead Engineer (90 mins)
- Zoom interview with our CEO (30 mins)
Equal Employment Opportunity statement (EEO)
Intenseye is committed to a policy of equal employment opportunity. We recruit, employ, train, compensate, and promote without regard to race, color, age, sex, ancestry, marital status, religion, national origin, physical or mental disability, sexual orientation, gender identity, medical condition, pregnancy, veteran status, genetic information or any other classification protected by state or federal law.