Generative AI Engineer at Knitit.ai in Palo Alto, California

Posted in Other 12 days ago.

Type: full-time





Job Description:

We are looking for a AI/ML Engineer to join a small team of ambitious people that are building an AI-powered assistant product in the Palo Alto, CA. We build innovative solutions that aim to amplify the power of our users through intelligent interactions. This position is ideal for a talented expert eager to apply their skills in the production of highly practical tools, advancing our AI Assistant products and solutions through innovative technology. This role is not research-based but rather focused on applying your theoretical knowledge and expertise directly into work going into the product, transforming theory into practice. The output of this position is customer facing and will be in everyday use by those who will come to depend on it.

This job requires continuous on-site work in Palo Alto, CA

Responsibilities:
  1. Develop innovative solutions and models based on Large Language Models and Natural Language Processing to enhance understanding and generation of natural language in our AI Assistant products.
  2. Stay on top of the current research in using LLM, and translate complex theoretical ideas into practical solutions for direct product implementations.
  3. Collaborate with cross-functional teams, integrating your models into the product pipeline
  4. Define evaluation metrics and monitoring performance, and take those learnings and apply them to optimize the customer experience and improvements in our products.
  5. Help define data acquisition, cleaning and exploration approaches


Qualifications:
  1. Bachelor's or Master's degree in Computer Science, Data Science, or relevant field.
  2. Minimum of 6 years of commercial experience in Data Science or a related field.
  3. Be able to work in person, daily in the office in the Palo Alto area
  4. Proven experience with Large Language Models and Natural Language Processing technologies, both API based like OpenAI and open source models.
  5. Strong programming skills in Python and familiarity with data science libraries and frameworks.
  6. Demonstrated ability to drive product-oriented results in data science.
  7. Exceptional problem-solving and analytical skills.
  8. Ability to work collaboratively in a team and communicate complex ideas effectively.
  9. Strong knowledge of machine learning algorithms, statistical modeling techniques, and application to real-world tasks.
  10. Proficiency in handling and manipulating large datasets.

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