Senior Machine Learning Platform Engineer...
Role details
Job location
Tech stack
Job description
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Form a deep understanding of our Machine Learning Engineers' needs and our current capabilities and gaps.
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Mentor our talented junior engineers on how to build high quality software, and take their skills to the next level.
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Continually raise our engineering standards to maintain high-availability and low-latency for our ML inference infrastructure that runs both predictive ML models and LLMs.
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Optimize low latency streaming pipelines to give our ML models the freshest and highest quality data.
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Evangelize state-of-the-art practices on building high-performance distributed training jobs that process large volumes of data.
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Build tooling to observe the quality of data going into our models and to detect degradations impacting model performance.
Requirements
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5+ yrs of industry experience as a Software Engineer.
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You have a strong understanding of distributed systems.
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You lead by example through high quality code and excellent communication skills.
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You have a great sense of design, and can bring clarity to complex technical requirements.
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You treat other engineers as a customer, and have an obsessive focus on delivering them a seamless experience.
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You have a mastery of the fundamentals, such that you can quickly jump between many varied technologies and still operate at a high level.
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Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.
Nice to haves:
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Experience building ML models and working with ML systems.
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Experience working on a platform team, and building developer tooling.
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Experience with the technologies we use (Python, Golang, Ray, Tecton, Spark, Airflow, Databricks, Snowflake, and DynamoDB).