Senior AI/ML Engineer

Job not on LinkedIn

🕒 August 4

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Logo of The Disruptors Den

The Disruptors Den

51 - 200 employees

Founded 2023

🤝 B2B

🌍 Social Impact

B2B • Startup • Social Impact

The Disruptors Den is an organization that focuses on innovation and entrepreneurship, providing a platform for startups and new ideas to thrive. It serves as a community for disruptors and visionaries seeking to challenge the status quo and drive change in their respective industries. The goal of The Disruptors Den is to connect like-minded individuals and foster an environment conducive to growth and collaboration.

📋 Description

• Own the competency navigation algorithm behind the Learner-Competency-Mapper, including its design, implementation, and update dynamics as real data arrives • Encode the prerequisite structure of the domain and its priors so the model performs from a cold start and improves as learners progress • Build pipelines that turn unstructured platform data into signal • Develop a constrained LLM-as-judge to assess whether Chidi is effective, including model selection, evaluation design, and awareness of judges’ failure modes • Build behavioural and at-risk profiling and models that evaluate learners for the Grader-Competency-Pulser as platform feedback data accumulates • Grow the platform’s capabilities into genuine ML and data-science work as the data asset develops

🎯 Requirements

• Real depth in probabilistic/Bayesian modelling, including designing models from domain structure rather than only fitting them to data • Strong Python skills and ability to ship production pipelines, not just notebooks • Evaluation design experience or judgment to build evaluation systems quickly • Serious probabilistic modelling of structured domains such as recommenders, knowledge graphs, or causal inference • Careful reasoning about assumptions and cold-start model priors • Ability to learn unfamiliar domains quickly • Ability to discuss a model that was wrong and how it was evaluated • BKT/KST or psychometrics exposure (desirable, not required) • MLflow or similar experiment tracking (desirable, not required) • Knowledge graphs (desirable, not required) • Self-drive and work ethic for small-team and virtual collaboration • Constant communication using web collaboration and video conferencing • Willingness to continually develop capabilities and attain certifications

🏖️ Benefits

• Virtual working • Encouragement to continually develop capability and attain certifications • Interaction with colleagues and customers in different physical locations internationally

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