Staff Machine Learning Infrastructure Engineer

PlaylabRemote

Remote Full-time

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Experience Level

Mid to Senior

Qualifications

We are looking for candidates with a strong background in machine learning, software engineering, and data engineering. Familiarity with cloud services such as AWS, GCP, or Azure is essential. Candidates should have experience with building scalable data pipelines and ML infrastructure, as well as proficiency in programming languages such as Python, Java, or Scala. Strong problem-solving skills and a passion for educational technology are also critical.

About the job

About Playlab

Playlab is a pioneering tech non-profit committed to empowering educators and students to become critical consumers and creators of artificial intelligence (AI).

We advocate for an open-source, community-driven approach as essential for unlocking the potential of AI in education. Our mission is to equip communities with AI tools and provide hands-on professional development, enabling educators and students to develop custom AI applications tailored to their unique environments. Over 60,000 educators have already published applications on Playlab, and our impact continues to expand daily.

At Playlab, we view AI as a new design material, one that should be shaped collectively to realize innovative ideas about learning. If you share our passion for constructing equitable and creative futures for students and educators, we invite you to join our team.

The Role

We are looking for a Staff Machine Learning Engineer to join our expanding Engineering team. In this role, you will design the systems that ensure AI remains accessible as we grow, balancing advanced capabilities with cost-effectiveness, driving research into effective educational AI, and paving the way for sophisticated AI to operate globally.

Examples of the Work

Develop data pipelines that scrub Personally Identifiable Information (PII), create research datasets, and support the research portal for educational AI initiatives.
Architect pathways for self-hosted and on-device model deployments to enhance privacy and global accessibility.
Design and implement model orchestration systems that intelligently route requests among various AI providers (OpenAI, Anthropic, AWS Bedrock, open-source models).
Establish cost optimization infrastructures, implementing conversation compression, prompt caching, and smart model selection to maintain AI accessibility.
Create comprehensive observability systems for ML operations, monitoring costs, latency, quality, and usage patterns across thousands of applications.
Design and implement infrastructure for fine-tuning and deploying custom models.
Build monitoring and alerting systems to ensure reliability as AI interactions scale.
And more…

Expectations

Design, build, and maintain production ML infrastructure that balances performance, cost, and reliability.
Take ownership of data quality and research dataset creation, ensuring data is properly scrubbed, documented, and useful.

About Playlab

Playlab is dedicated to transforming the educational landscape through AI. By providing innovative tools and resources, we empower educators and students to leverage AI technology to create impactful learning experiences. Our commitment to community-driven solutions ensures that our approach is inclusive and effective across diverse educational contexts.

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