AI Engineer for Large Language Model Development
7 days ago
We are a pioneering company in the field of artificial intelligence, dedicated to transforming spoken communication for individuals, teams, and organizations. Our mission is to harness the power of large language models to revolutionize the way people interact and collaborate. At Supernormal Technologies, Inc., we value innovation, creativity, and a strong work ethic.
Role OverviewThe successful candidate will join our AI team as a Machine Learning Engineer, responsible for developing and deploying cutting-edge large language models that superpower our core product experience. This role involves working closely with cross-functional teams to design, build, and maintain reliable and secure services that utilize the most advanced AI models in the market. The ideal candidate will possess a strong background in machine learning, software engineering, and Python programming.
Key Responsibilities- Prominent responsibilities include leading the full development cycle of AI solutions for meeting notes, question answering, agent conversations, and task completion. As an ML Engineer, you will be tasked with prompt engineering, agentic workflows using LLM APIs, custom model training, fine-tuning, and optimizing deployment for cost, latency, and quality.
- Design and implement novel approaches to improve the core meeting assistant scenarios, leveraging state-of-the-art techniques such as prompt engineering.
- Develop and deploy machine learning models to enhance transcript quality, reduce API token usage, eliminate LLM output defects, and extract semi-structured data.
- Train and deploy custom language models (LoRA, RLHF, instruction-tuning, etc.) for diverse business needs, fine-tuning models to optimize performance.
- Create new NLP & LLM-driven product experiences that continuously improve with user feedback, collaborating with product and design teams.
- Improve our LLM-powered search and question answering using retrieval augmented generation (RAG), defining and optimizing quality metrics, and streamlining infrastructure.
- Demonstrated proficiency in AI/ML with a minimum 3-5 years of experience building machine learning systems, showcasing production-level expertise.
- Experience delivering products and services using GenAI: at least 1 year of experience building NLP systems using LLMs, including proficiency in data curation/cleaning/labeling, fine-tuning/training models, and evaluating generative text output.
- A solid engineering background with a robust foundation in software engineering principles, exhibiting comfort and excellence in writing code for and supporting production engineering systems.
- A Bachelor's degree in Computer Science, Engineering, AI, Mathematics, or related field; Master's degree or PhD a plus.
- Proficient in Python: our AI stack uses Python and interfaces with Ruby on Rails and Typescript (bonus if you know these, but not required).
- A competitive salary range between $120,000 and $180,000 per year.
- An annual WFH budget to ensure your home workspace meets your needs.
- Education credit (up to $500 per year).
- Unlimited PTO (minimum 4 weeks).
- Honest and timely feedback. We're all better when we can have candid conversations about what is and isn't working.
- A willingness to listen to your ideas: how can the codebase, our product, or team be better?
We're a fully distributed team spread between Pacific Time (California) and Central European Time (Stockholm) with lots of places in between. We'll see you most days in Slack, Google Meet, GitHub issues, and Notion. Sometimes in person in a place with a warm breeze.
We're a friendly bunch and are happy to pair, talk through, or otherwise assist any time. Respect for your time outside of work is also a priority here – we all work hard, but we never forget to rest and have fun.
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