WebAI

About WebAI

Democratizing AI with customizable, local models

👥 21-100 employees📍 Congress Avenue Historic District, Austin, TX💰 $77m
B2BArtificial IntelligenceMachine LearningSaaSCloud Computing

Key Highlights

  • $77 million raised in seed funding to date
  • Decentralized platform minimizes data requirements for AI models
  • Unlimited PTO and flexible work week for employees
  • Located in Congress Avenue Historic District, Austin, TX

webAI is an Austin-based startup focused on revolutionizing the AI industry by providing a decentralized development platform that minimizes data requirements for building AI models. With $77 million in funding, webAI aims to democratize artificial intelligence by enabling enterprises to create cust...

🎁 Benefits

webAI offers unlimited PTO, performance-based incentives, and a comprehensive health benefits package that includes dental and vision coverage. Employ...

🌟 Culture

webAI fosters a culture centered on democratizing AI, challenging the notion that large datasets are essential for effective AI. The company emphasize...

WebAI

Machine Learning Engineer Staff

WebAIAustin - On-Site

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Skills & Technologies

Overview

WebAI is hiring a Staff Machine Learning Engineer to lead the development of advanced AI models, focusing on Large Language Models and Mixture of Experts. You'll work with Python and machine learning frameworks like TensorFlow and PyTorch in Austin.

Job Description

Who you are

You have a Ph.D. in Computer Science or a related field, and at least 5 years of experience in machine learning, specifically with Large Language Models and Mixture of Experts. Your proven track record includes developing and deploying advanced AI models, showcasing your ability to innovate in the field. You possess strong programming skills in Python and are proficient with machine learning frameworks such as TensorFlow and PyTorch. Your expertise is complemented by a commitment to staying updated on the latest advancements in AI and ML, allowing you to apply cutting-edge techniques to improve model performance and efficiency.

You are a natural collaborator, eager to work with cross-functional teams to integrate machine learning models into a decentralized AI development platform. Your mentoring skills shine as you guide junior engineers, fostering a culture of knowledge sharing and best practices within the team. You thrive in a dynamic environment where your contributions can directly impact the growth and success of the organization.

Desirable

Experience with publications or significant industry contributions will set you apart. Familiarity with decentralized AI systems and a passion for pushing the boundaries of what AI can achieve will enhance your fit for this role.

What you'll do

In this role, you will lead the development and optimization of Large Language Models and Mixture of Experts models, ensuring they meet the high standards required for deployment in real-world applications. You will collaborate closely with engineering and product teams to integrate these models into our platform, driving innovation and efficiency. Your research efforts will focus on cutting-edge machine learning techniques, with the goal of enhancing the performance of our AI models.

You will stay abreast of the latest advancements in AI and ML, applying this knowledge to refine our methodologies and improve our models. Mentoring junior engineers will be a key part of your responsibilities, as you share your expertise and help them grow in their careers. You will contribute to the team's knowledge base, ensuring that best practices are documented and shared across the organization.

What we offer

At webAI, you will be part of a fast-growing team that values a fun and growth-oriented office culture. We offer competitive compensation and opportunities for professional development. You will have the chance to work on groundbreaking technology that challenges traditional assumptions about AI and data. Join us in shaping the future of AI development and making a meaningful impact in the industry.

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