Machine Learning Engineer
Company: Aitopics
Location: San Francisco
Posted on: November 14, 2024
Job Description:
SupernormalSupernormal is your AI-powered meeting platform.
Automate meeting notes, agendas, and insights, while Voice Agents
help you scale tasks effortlessly-empowering teams to focus on what
matters most: building genuine connections and driving.We're on a
mission to transform spoken communication for individuals, teams,
and organizations. Meetings are an information-rich channel for
productivity, but much is lost due to lack of structure and
information flow. At Supernormal we're solving this problem with
focus, design, and craft.Supernormal is a remote-first company and
does not require co-location. We have annual team retreats and
gatherings several times a quarter.About the roleMachine learning
engineers at Supernormal build the AI that superpowers the core
product experience for people's meetings including transcription,
note generation, and task automation. The AI team builds reliable
and secure services that use the most advanced AI models in the
market to generate millions of high-quality meeting notes to a
rapidly growing customer base. Our work revolves heavily around
software engineering, too - we are looking for people with a drive
to roll up their sleeves and get new models and features out to
users as quickly as possible.What you'll work onAs an ML Engineer
on Supernormal's AI team, you'll lead the full development cycle of
AI solutions for meeting notes, question answering, agent
conversations, and task completion. Your responsibilities will
include:
- Prompt engineering using state-of-the-art techniques to improve
the core meeting assistant scenarios.
- Building and shipping machine learning models to improve
transcript quality, reduce API token usage, eliminate LLM output
defects, and extract semi-structured data.
- Training and deploying custom language models (LoRA, RLHF,
instruction-tuning, etc.), fine-tuning models for diverse business
needs.
- Creating new NLP & LLM-driven product experiences that improve
with user feedback, collaborating with product and design
teams.
- Improving our LLM-powered search and question answering using
retrieval augmented generation (RAG), everything from defining and
improving quality metrics to optimizing our infrastructure.
- Advocating for, and building, new and better ways of doing
things.RequirementsWhat you will bring
- Production-level AI/ML Experience: Demonstrated proficiency in
AI/ML with a track record of at least 3-5 years experience building
machine learning systems.
- Experience delivering products and services using GenAI: 1+
year experience building NLP systems using LLMs.
- Software Engineering Competency: A solid engineering background
with a robust foundation in software engineering principles.
- A Solid Educational Foundation in AI/ML: Bachelor's degree in
Computer Science, Engineering, AI, Mathematics, or related
field.
- Proficient in Python: our AI stack uses Python and interfaces
with Ruby on Rails and Typescript.What we'll expect of you
- A collaborative mindset, focused on lifting others and
improving daily.
- A drive to tackle tough problems and do hard things.
- High agency and initiative in bringing and building ideas.
- Willingness to learn and improve existing approaches.
- Emphasis on shared ideas and collective responsibility.
- A growth mindset when facing challenges, aiming for team
improvement.What you can expect from us
- We're a fully distributed team spread between Pacific Time
(California) and Central European Time (Stockholm).
- We're a friendly bunch and are happy to pair, talk through, or
otherwise assist any time.
- Honest and timely feedback.
- A willingness to listen to your ideas.
- A respect for your time outside of work.Full healthcare
coverage (Medical, Dental, and Vision)Totally remote. Not hybrid.
Remote. No return-to-office here.WFH budget to make sure you have
everything you need to do your best work.Education credit (up to
$500 per year).
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Keywords: Aitopics, Fairfield , Machine Learning Engineer, Engineering , San Francisco, California
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