Senior Software Engineer, ML Platform
Overview
You will own the evolution of our ML Platform, building reliable systems for model experimentation, training, evaluation, inference, and retraining that underwrite small businesses. You will join the Infrastructure team, collaborating with data scientists and product engineers to ship developer-friendly tooling. This role stands out because you will set the technical direction for our ML infrastructure, impacting every model-driven decision in the company.
What You'll Do7
- 1Design and build scalable ML pipelines for training and evaluation using Python and Kubernetes.
- 2Ship a model registry and feature store that enable reproducible experiments and seamless deployment.
- 3Optimize inference serving with TensorFlow and PyTorch to reduce latency and cost.
- 4Lead the migration of legacy training jobs to AWS managed services, cutting maintenance overhead.
- 5Automate model retraining triggers based on data drift detection, ensuring models stay current.
- 6Develop internal dashboards for monitoring model performance and resource usage, giving teams actionable insights.
- 7Drive adoption of best practices in MLOps, including CI/CD for ML artifacts and versioning.
Requirements6
- 15+ years building production-grade ML platforms or infrastructure.
- 2Strong proficiency in Python and experience with Kubernetes and Docker.
- 3Hands-on experience with AWS services like S3, EC2, and Lambda.
- 4Familiarity with TensorFlow or PyTorch for model training and serving.
- 5Proven track record of designing reliable, low-latency systems at scale.
- 6Excellent communication skills and ability to mentor junior engineers.
Salary Insight
Salary not disclosed in listing
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