Realeyes is looking for a Senior ML Ops Engineer to join the Computer Vision team. This team works on cutting edge machine learning problems that are at the core of our business. The engineers within the team work with large amounts of video, image and biometric data to continually enhance and innovate the core technology stack.
We are looking to hire a motivated, best-in-class Senior ML Ops Engineer to create and maintain our systems and tools to optimize and improve Realeyes capabilities in computer vision.
Our ideal candidate is highly autonomous, detail orientated, possesses strong written and verbal skills, and has significant experience supporting large scale, enterprise class products and tooling. The desire to work in a fast-paced, collaborative environment is essential. They will help shape the architecture and development of cloud-native applications and tools that are used by our researchers and products as part a diverse, cross-functional team.
- Work in tandem with our researchers and computer vision engineers to identify, design and implement cloud-based solutions.
- Define and document best practices and strategies regarding application deployment and infrastructure maintenance.
- Ensure application performance, uptime, and scale, maintaining high standards of code quality and design.
- Managing cloud infrastructure in accordance with regulatory guidelines.
- Troubleshoot incidents, identify root cause, fix and document problems, and implement preventive measures.
- 3+ years of experience architecting, designing, developing, and implementing cloud solutions on AWS.
- Detailed working knowledge of core AWS services: S3, Lambda, IAM, SQS, SNS and CloudWatch.
- Experience in several of the following areas: database architecture, ETL, business intelligence, big data, machine learning or advanced analytics.
- Experience writing and maintaining infrastructure-as-code in CloudFormation, Serverless or Terraform.
- CI/CD experience using CodePipeline and CodeBuild.
- AWS certifications are a plus.
- Machine learning/SageMaker experience.
- Linux system administration.
- Cross-account AWS infrastructure/architecture.
- Docker containers on ECS/Fargate.
- Experience of working with regulated data (GDPR etc).
What we offer
- a great opportunity to work in a young but well-established international company where what you do has a direct and immediate impact
- unlimited holidays
- life insurance and 100% paid sick leave
- working from home option for which we’re providing the necessary equipment (office table, chair, monitor etc.)
- flexible working hours
- possibility to participate in our company share option program
- budget for professional development
- strong benefits package including subsidized gym membership/healthy living allowance, frequent team-building and social events
We highly support remote work but for this position it's essential to work in GMT Time Zone +/- 2 hours. Please note that if you are outside of this you will be automatically rejected.