
AI Infrastructure Engineer
2 days ago
We are building a futuristic AI platform to revolutionize the waste industry by harnessing data from waste. This cutting-edge system will drive automation and digital transformation across the sector, unlocking efficiencies and fostering sustainability at scale.
The successful candidate will play a leading role in shaping our technical infrastructure and product success as an early engineering hire.
- Design, build, and maintain robust pipelines for processing image and video data, running ML model inferences, and serving results efficiently.
- Architect, implement, and manage scalable and reliable infrastructure for data storage, model deployment (CI/CD), and inference serving on cloud platforms.
- Work closely with frontend and product teams to design and implement backend services and APIs that power responsive, data-driven UI experiences.
- Manage databases, implement background task processing and access control.
- Implement monitoring, logging, and alerting systems; manage secrets securely; ensure system scalability and stability through automated deployments and rollbacks.
- Help establish and advocate for MLOps/Platform best practices within the team.
- 5+ years of proven experience in MLOps, AI/ML Infrastructure, Platform Engineering, or a related Backend Engineering role.
- Strong programming skills, particularly in Python, and deep experience with ML frameworks.
- Extensive hands-on experience with CI/CD practices, containerization (e.g., Docker), and cloud platforms.
- Proven experience designing and managing data storage solutions (databases, cloud storage) and messaging/queuing systems in production.
- Solid understanding and application of software engineering best practices (testing, version control, etc.).
- Demonstrable experience building, deploying, and maintaining scalable, production-grade systems.
- Ability to work independently, take initiative, own projects end-to-end, and drive them to completion in a fast-paced, evolving startup environment.
- Proficiency in English.
- Experience with high-availability systems and real-time data processing.
- Familiarity with Infrastructure-as-Code tools.
- Mild familiarity with Go (Golang) and/or JavaScript (JS).
- Experience scaling systems and processes within a startup environment, ideally seeing growth from Seed or Series A stages.
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