We're Hiring: Senior MLOps Engineer

We’re looking for a Senior MLOps Engineer to take ownership of the design, scaling, and maintenance of the infrastructure powering our machine learning models and workflows.

You’ll work closely with top-notch ML engineers and data scientists to ensure our systems are fast, reliable, and continuously improving.

What you’ll do

• Collaborate with a high-performing ML team to deploy new models to production
• Build, deploy, and maintain computer vision and LLM models in production across multi-cloud environments (GCP, Modal.com)
• Own real-time and batch ML pipeline orchestration using Dagster
• Optimize compute (CPU/GPU) and memory usage to balance performance and cost
• Support the transition of models from prototype to production
• Develop automated systems for model training, testing, and deployment
• Maintain interactive dashboards (e.g., Streamlit) for model performance and drift monitoring
• Evaluate and integrate new tools and technologies for scale, speed, and robustness
• Contribute to future infrastructure for agentic workflows, document analysis, and ML-based decision-making

Basic Requirements

• Proven experience deploying and maintaining ML models in production
• Strong Python skills – comfortable working with complex, messy codebases
• Deep understanding of compute and memory resource management, including GPU-based environments
• Hands-on experience with Docker and Kubernetes (strong advantage)
• Experience with model serving frameworks (TorchServe, BentoML, FastAPI)
• Familiarity with ML CI/CD workflows (e.g., GitHub Actions, Terraform)
• Practical experience with cloud platforms – especially GCP – and modern ML infrastructure