We’re Mitek, a NASDAQ-listed global leader in mobile capture and digital identity verification solutions built on the latest advancements in AI and machine learning. Our Mobile Verify and Mobile Deposit products power and protect millions of identity evaluations and mobile deposits every day, around the world.
Our future of work is about enabling a smarter, faster, and happier workforce regardless of work location. Whether you prefer to work from a Mitek office or a remote location of your choosing, we'll provide you with the digital excellence, supporting systems & tools, and communication transparency that allows you to do your best, most collaborative work.
Mitek is seeking a Software Engineer to help scale and improve our AI development life-cycle.
The candidate will work closely with Research to build, maintain and deploy infrastructure, tools, and automation to support our Machine Learning Data processes and practices, from Data annotation and curation processes to delivering and monitoring AI Models to production.
The ideal candidate is someone with a strong development background in a Cloud-based environment. The candidate will help leverage Cloud vendor products to develop tools, processes, and automation to support Mitek’s goal to streamline its Data & Machine Learning vision.
A successful candidate must have great communication skills, be passionate, think outside the box, be customer-oriented, and have a sense of ownership. A proven track record of designing, developing, and maintaining dependable, mission-critical systems and products is a must.
What You'll Do
- Continuously improve the Machine Learning infrastructure, tools, and practices in order to easily and quickly deploy, scale, and adapt to organizational needs.
- Build and innovate tools and automation to replace manual processes, deployments, and operational tasks related to Machine Learning Data and Model Lifecycle needs.
- Development of deep insight into Machine Learning data pipelines and framework.
- Build and maintain data management ecosystem for AI/ML Lifecycle including but not limited to collection and sourcing pipeline, annotation and curation system, dataset management, storage, and distribution.
- Create processes that enhance operational ML workflows and provide positive customer impact.
- Work with Research & Engineering teams on ML model development by resolving issues related to ML model pipelines, deployment, optimization, or debugging.
What You Need
- Experience writing applications, tools, and automation with Python.
- Experience in developing solutions based on Cloud services such as Amazon Web Services (AWS).
- Experience in Infrastructure automation (e.g Terraform or CloudFormation)
- Experience with Databases (e.g. MySQL, DynamoDB, MongoDB), and Database Management at scale.
- Experience in the implementation of distributed systems based on a serverless technology or micro-services architecture and a passion for quality engineering
- Knowledge of continuous integration and delivery (CI/CD)
- Excellent English communication and teamwork skills.
- Understanding of agile methodologies and practices.
What Would Be Nice To Have, But Not Required
- Experience in High-Performance Computing(HPC) or Machine Learning infrastructure and tools (eg AWS SageMaker / Lustre / Batch)
- AWS / Python Certified.