Job Description
MLOps and Data Engineer
We are hiring for a fast-growing well funded 25 person start-up at the forefront of generative video technology. We’re looking for a Senior MLOps & Data Engineer to join their growing team.
What You'll Do
- Own and evolve our ML data and training pipelines — from ingestion to deployment — ensuring they are scalable, efficient, and reliable
- Build, deploy, and maintain distributed training jobs (e.g. with Megatron or other frameworks) across multi-node clusters
- Design and manage robust data processing workflows, supporting both real-time and batch operations
- Collaborate closely with research and engineering teams to bring ML models from prototype to production
- Optimize inference pipelines for low-latency, cost-effective serving
- Monitor and improve system performance, reliability, and security across the ML lifecycle
Key Qualifications
- 4+ years of experience in MLOps, ML infrastructure, or data engineering roles
- Hands-on experience deploying and maintaining distributed training jobs on GPU clusters
- Deep understanding of MLOps best practices and tools (CI/CD for ML, experiment tracking, versioning, etc.)
- Strong experience with AWS or GCP
- Proficiency in Python and common data/ML tooling (e.g., PyTorch, TensorFlow, Airflow, Kubeflow, etc.)
- Experience with inference optimization for large models, focusing on latency, throughput, and cost
- Strong systems design skills, including distributed systems, orchestration, and monitoring
- Bonus: Experience with Megatron , TPU/GPU optimization , or similar large-model training frameworks
Please apply for more details
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