Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Collaborate with data scientists and research/machine learning engineers to deliver products to production.
- Build and maintain data pipelines for analytics, model evaluation and training (includes versioning, compliance and validation)
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, equity, inclusion, and respect
- Build backend interfaces leveraging modern web stacks
- Build and automate and maintain our AI/ML data pipelines & workstream from data analysis, experimentation, model training, model evaluation, deployment, operationalization, and tuning to visualization
- Improve and maintain our automated CI/CD pipeline while collaborating with our stakeholders, various testing partners and model contributors
- Increase our deployment velocity, including the process for deploying models and data pipelines into production
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in Python Programming, OOP, Databases and Big Data
- Experience with REST API, Cloud, Micro services, and other web technologies
- Experience in AWS cloud and services (S3, Lambda, Aurora, ECS, EKS, SageMaker, Bedrock, Athena, Secrets Manager, Certificate Manager etc.)
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Overall knowledge of the Software Development Life Cycle
- Proven DevOps/MLOps experience provisioning and maintaining infrastructure leveraging some of the following: Terraform, Ansible, AWS CDK, CloudFormation
- Experience in some of the following technologies Hadoop, PySpark, AWS Cloud, AWS DynamoDB, AWS Lambda, Terraform
- Experience in containerization and infrastructure as code Docker/Kubernetes/Terraform
- Experience with CI/CD pipelines example Jenkins/Spinnaker
Preferred qualifications, capabilities, and skills
- Familiar with monitoring tools such as Prometheus, Grafana, Splunk and Datadog
- Strong commitment to development best practices and code reviews
- Strong interpersonal skills; able to work independently as well as in a team
- Experience with deep learning frameworks such as TensorFlow or Pytorch
- Experience with data labelling, validation, provenance and versioning
- Any cloud certifications