About the Role
You architect and implement distributed and cloud based systems that support the full machine learning lifecycle from data ingestion and preprocessing to model training deployment and monitoring. You develop and maintain robust backend services and APIs in Python or Go. You optimize compute storage and data retrieval using relational NoSQL and vector databases to enable low latency model inference. You collaborate with stakeholders to deliver AI driven capabilities in domains such as market data trading authentication and security. You leverage cloud infrastructure AWS or GCP and container orchestration technologies Docker and Kubernetes to manage large scale compute environments for AI workloads. You design and maintain automated CI/CD workflows to ensure efficient and reliable code delivery. You implement model serving and observability systems to monitor performance ensure fault tolerance and improve system reliability. You apply algorithms and data structures to enhance compute and data efficiency across the ML infrastructure stack. You prototype and evaluate new AI tools frameworks and system designs to validate concepts and optimize performance prior to large scale rollout. You drive continuous improvement by identifying opportunities for scalability performance and cost optimization. You contribute to open source projects where possible and uphold software engineering best practices including code reviews automated testing and version control in an agile environment. Telecommuting permitted.
Requirements
- Bachelor’s degree or foreign academic equivalent in Computer Science or a related field.
- Kubernetes
- Spark
- Machine Learning
- Python
- Databases
- AWS
- Background checks required
Responsibilities
- Architect and implement distributed and cloud-based systems that support the full machine learning lifecycle - from data ingestion and preprocessing to model training, deployment, and monitoring.
- Develop and maintain robust backend services and APIs (RESTful and gRPC) in programming languages such as Python or Go.
- Optimize compute, storage, and data retrieval systems using relational, NoSQL, and vector databases to enable low-latency model inference and intelligent data access.
- Collaborate with cross-functional stakeholders to deliver AI-driven capabilities in domains such as market data, trading, authentication, and security.
- Leverage cloud infrastructure (e.g., AWS or GCP) and container orchestration technologies (e.g., Docker, Kubernetes) to manage large-scale compute environments for AI workloads.
- Design and maintain automated CI/CD workflows to ensure efficient and reliable code delivery.
- Implement model serving and observability systems to monitor performance, ensure fault tolerance, and improve system reliability.
- Apply algorithms and data structures to enhance compute and data efficiency across the ML infrastructure stack.
- Prototype and evaluate new AI tools, frameworks, and system designs to validate concepts and optimize performance prior to large scale rollout.
- Drive continuous improvement by identifying opportunities for scalability, performance, and cost optimization.
- Contribute to open-source projects (where possible) and uphold software engineering best practices including code reviews, automated testing, and version control in an agile environment.
- Telecommuting permitted.
Benefits
- Challenging, high-impact work to grow your career
- Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
- Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents
- Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
- Employer-paid life & disability insurance, fertility benefits, and mental health benefits
- Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
- Exceptional office experience with catered meals, events, and comfortable workspaces.