Job description:

We are looking for a talented and driven developer to join our Research Engineering team and contribute to the development of scalable, cloud-native AI solutions on AWS. This role focuses on building and maintaining infrastructure and services that support advanced machine learning workflows, real-time inference, and robust observability.

What is your mission?

• Research and build data-driven applications
• Research and develop Machine Learning algorithms to turn forensic data into investigation leads, evidence, and intelligence insights
• Be a part of a heterogeneous, multi-disciplinary research team
• Take projects end to end, from the inception of the idea, through data and algorithm research and POC development
• The work is both analytical and experimental in nature and includes prototyping of new algorithms, investigating data, and evaluating algorithm performance

Responsibilities

• Design and implement features for our AWS-based AI solution, including job orchestration, manifest generation, and API integrations
• Develop and maintain CI/CD pipelines using GitHub Actions, CDK, and AWS infrastructure (e.g., SageMaker, Lambda, Bedrock)
• Ensure code quality and reliability through comprehensive unit testing, performance testing, and observability enhancements
• Collaborate with cross-functional teams to integrate AI services into broader investigation workflows and runtime environments
• Troubleshoot deployment issues and contribute to the continuous improvement of dashboards and monitoring tools

Required Skills

• Proficiency in Python and Typescript, with experience in API development and cloud-native architectures
• Hands-on experience with AWS services including SageMaker, Lambda, etc.
• Experience with machine learning libraries such as PyTorch, Pandas, NumPy, and related data processing tools
• Ability to write clean, maintainable code and contribute to shared documentation and best practices
• Familiarity with GitHub workflows, secrets management, and secure deployment practices
• Familiarity with Amazon EKS and Kubernetes-based deployments

Preferred Qualifications

• Experience with GenAI infrastructure, semantic caching, and LLM integration
• Knowledge of observability tools like Datadog and log aggregation strategies
• Prior contributions to scalable AI platforms or high-throughput batch processing systems

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