Position Overview
We are looking for a senior backend software engineer to join machine learning platform engineering team. In this role, you will be responsible for the development and expansion of core infrastructure supporting company’s AI/ML products. You will partner closely with data scientists and machine learning engineers to design and deliver state-of-the-art AI/ML infrastructure, with a strong focus on deploying and productionizing models across multi-cloud and hybrid environments. The contract offering the opportunity to continually challenge yourself, expand your skillset, own your work.
What You Will Do
- Technical Contributions: Design, develop, test, and release software and infrastructure supporting AI/ML and experimentation workflows.
- Model Deployment & Productionization: Design, develop, and deploy ML models into production across AWS, GCP, Azure, and on-prem environments.
- Scalable Pipelines: Build scalable, high-throughput ML pipelines supporting multi-GPU and distributed training/inference.
- Infrastructure & Deployment: Implement robust deployment strategies using Docker, Kubernetes, Terraform, and CI/CD workflows. Deploy services into AWS and Kubernetes environments and participate in an on-call rotation.
- Optimization: Optimize model serving for LLMs and Generative AI applications, ensuring low latency and high availability. Apply model inference optimization, GPU acceleration, and parallel processing techniques.
- Collaboration: Work closely with data scientists, MLOps, platform engineering teams, and product managers to operationalize models and become a valued member of an autonomous, cross-functional team.
- Monitoring & Best Practices: Ensure monitoring, observability, and performance tuning of deployed models at scale. Drive best practices in model versioning, reproducibility, and compliance (including security and data governance).
- Code Review & Documentation: Grow our knowledgebase by participating in code reviews, writing, and reviewing documentation.
