Supernormal · 3 days ago

Machine Learning Engineer

Seattle, WA

Full-time

Onsite

Senior Level

3+ years exp

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Artificial Intelligence (AI)Software

Insider Connection @Supernormal

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Prompt engineering using state-of-the-art techniques to improve the core meeting assistant scenarios

Building and shipping custom machine learning models to augment the AI stack, including improving transcript quality, reducing tokens sent to APIs, removing defects in LLM output, and extracting semi-structured data

Training and deploying custom large language models from open source using state-of-the-art techniques (LoRA, RLHF, instruction-tuning, etc)

Developing new product experiences using NLP & LLMs that get better based on user feedback & iteration while collaborating with product engineers & design team

Defining and improving business & product metrics to optimize the quality and cost of AI usage

Improving LLM-powered search and question answering (using RAG) over sets of meetings

Advocating for, and building, new and better ways of doing things. You'll leave everything you touch just a bit better than you found it

Qualification

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AI/MLNLPLLMsData CurationModelingPythonSQLPyTorchRuby on RailsSnowflake

Required

Demonstrated proficiency in AI/ML with a track record of at least 3-5 years experience building machine learning systems, up to speed on the latest in NLP & LLMs, and proficient in data curation, modeling, and training models

Bachelor's degree in Computer Science, Engineering, AI, Mathematics, or related field; Master's degree or PhD a plus

A solid engineering background with a robust foundation in software engineering principles. You have written code for and supported production engineering systems

Proficient in Python and SQL: our AI stack uses Python & PyTorch and interfaces with Ruby on Rails (bonus if you know it, but not required) and we write a lot of SQL queries on top of Snowflake to pull data