Lead a team of young and bright MLOps Engineers in conducting research, design, and prototype MLOps practices, tools, and frameworks to expedite the machine learning lifecycle at MoneyLion.
Work in collaboration with Data Scientists, Data Engineers, and AI/ML Engineering teams to enhance cross-team workflows and reduce time to deployment.
Improve the level of automation in the development and deployment processes of machine learning.
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Develop and apply computational methods to analyse diverse biological datasets, including genomics, transcriptomics (bulk, single-cell, and spatial RNA-seq), and proteomics, connecting findings directly to target identification and mechanism-of-action studies.
Build and deploy machine learning and AI models to uncover biological patterns, prioritise therapeutic targets, and generate biomarker hypotheses that advance the drug discovery pipeline.
Proactively adopt and integrate agentic AI tools — including LLM-assisted coding, automated analysis pipelines, and AI-driven literature synthesis — to accelerate your own and the team's throughput, championing AI-augmented working and continuously improving in-house workflows and platforms.
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