SimpliSafe is looking to hire a Senior Machine Learning Engineer to drive the development and deployment of machine learning models, optimize ML workflows, and ensure scalable, reliable, and secure ML infrastructure to support their mission of making every home a safe home.
Requirements
- Deep hands-on experience with AWS or similar public clouds, including compute, networking, container orchestration, and observability stacks.
- Hands-on experience with CI/CD pipelines, Docker, Kubernetes, and infrastructure-as-code tools (e.g., Terraform, Cloud Formation).
- Proficiency in programming languages like Python, and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch).
- Solid understanding of ML lifecycle management, including experiment tracking, versioning, and monitoring.
- LLM application development, including prompt engineering and evaluation.
- Experience with Ray for inference, or pipeline orchestration
- Hands-on experience with deploying large language models (LLMs) to production.
Responsibilities
- Lead the architecture, deployment, and optimization of scalable ML model serving systems for real-time and batch use cases.
- Collaborate with data scientists, engineers, and stakeholders to operationalize ML models.
- Develop CI/CD pipelines for ML models enabling rapid, safe, and consistent model releases.
- Design, implement, and own comprehensive production monitoring for ML models/systems.
- Manage cloud infrastructure, primarily in AWS or other major public clouds, to support ML workloads.
- Drive best practices in model versioning, observability, reproducibility, and deployment reliability
- Serve in an on-call rotation as a first responder for software owned by your team.
Other
- 5+ years of experience in software engineering, data engineering, or a related field, with at least 3 years focused on MLOps or ML infrastructure.
- Strong communication skills for partnering with cross-functional technical and non-technical teams.
- Customer Obsessed
- Aim High
- No Ego
