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 or automation to replace manual processes, deployment, and operational tasks related to Machine Learning needs and processes.
- Development of deep insight into Machine Learning data pipelines and framework.
- Build and maintain data storage and delivery for Machine Learning.
- Implementation of system and service telemetry to improve reliability and availability.
- Provide build and deployment automation support (CI/CD) for Data management & Machine Learning tools, systems, and services.
- Collaborate and help build utilities and tools for internal use that enable your fellow Researchers to deliver new ML models safely at high speed and wide scale.
- Work with Research & Engineering teams on ML model development and resolving issues related to ML model configuration, deployment, optimization, or debugging.
- Create processes that enhance operational ML workflows and provide positive customer impact.
- Resolve problems at their root by implementing simple and repeatable solutions.
- Design automated systems management solutions with self-repair as the goal.
- Ensuring system security through industry best practices.
What You Need
- Excellent communication and teamwork skills.
- Understanding of agile methodologies and practices.
- Bachelor’s degree in computer science or related field.
- Data-driven and analytical mindset.
- Organizational skills.
- Fluent in English.
- Experience writing applications, tools, and automation with Python.
- Experience with Linux in development and production environment.
- Knowledge of developing effective API’s (REST).
- Experience with Amazon Web Services in a production environment.
- Experience with Databases (e.g. MySQL, DynamoDB, MongoDB), and Database Management at scale.
- Experience with Event-Driven / Serverless architecture.
- Experience with Docker and related infrastructure at scale.
- Experience in implementing and maintaining Continuous Integration and Continuous Delivery (CI/CD) pipelines.
- Experience in developing infrastructure and tools (e.g. Jenkins, Git)
- Experience in automation and self-service infrastructures(e.g Terraform or CloudFormation)
- Ability to work effectively with people of all levels of information technology expertise with a wide range of constituencies and organizational relationships.
What Would Be Nice To Have, But Not Required
- Solid and successful background in participating in architecture, automation, and infrastructure designs and decisions on cloud and on-premise.
- Experience in High-Performance Computing(HPC) or Machine Learning infrastructure and tools.
- Experience with operational monitoring tools such as ElasticSearch, Kibana, Grafana, Zabbix, Prometheus.
- Experience with AWS SageMaker.
- AWS Certified.
- Python Certified.