Machine Learning Engineer building the Enterprise Brain - a proactive AI system for task detection, automation, reasoning, planning and personalization using LLMs, RL, fine-tuning, and advanced ranking on top of enterprise and personal knowledge graphs. Requires 3+ years ML experience, strong production ML skills, and expertise in evaluation/benchmarking.
200k – 300k/yr
Hybrid3+ YOEML Engineering
About the role
Responsibilities
Work on deeply challenging ML problems involving user understanding and task prediction.
Invent new LLM workflows and signals to improve reasoning, planning, and personalization.
Design and optimize reinforcement learning and fine-tuning approaches to improve the quality of understanding, prediction and other agentic systems.
Lead development of scalable evaluation, benchmarking, and optimization loops.
Build and maintain robust ML pipelines for enterprise and knowledge graph construction.
Drive initiatives to measure, monitor, and improve data quality, model quality, and end-to-end system performance.
Collaborate with cross-functional teams to deeply understand customer pain points and deliver high-quality, production-ready ML solutions.
Mentor junior engineers or learn from experienced ones in a tight-knit, high-velocity environment.
Requirements
3+ years of industry experience in AI or Machine Learning Engineering.
BA/BS in computer science, math, sciences, or a related field.
Experience with search, recommendation, natural language processing, or other large-scale ML systems.
Proven ability to design, build, and ship production-ready models and systems.
Demonstrated expertise in ML evaluation, benchmarking, and data quality—ideally with experience in building or maintaining evaluation frameworks for complex enterprise tasks.
Proficiency in your ML framework of choice (e.g., TensorFlow, PyTorch).
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