Staff Machine Learning Engineer

7 days ago

Austin, TX, United States webAI Inc Full time
About Us:

webAI is a software company that is building a decentralized AI development platform. Our technology enables the development of powerful AI using limited amounts of data, challenging the underlying assumption that big data is the key to unlocking the full power of AI. webAI offers opportunities to join a dynamic and fast-growing team that fosters a fun and growth-oriented office culture.

About the Role:

We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models (LLMs) and/or Mixture of Experts (MoEs). The ideal candidate will have a proven track record of developing and deploying advanced AI models.

Responsibilities:
  • Lead the development and optimization of Large Language Models and Mixture of Experts models.
  • Collaborate with cross-functional teams to integrate ML models into our platform.
  • Conduct cutting-edge research in machine learning, with a focus on improving the performance and efficiency of LLMs.
  • Stay abreast of the latest advancements in AI and ML, and apply this knowledge to improve our models and methodologies.
  • Mentor junior engineers and contribute to the team's knowledge sharing and best practices.
Qualifications:
  • Advanced degree (Ph.D. preferred) in Computer Science, or a related field.
  • Proven track record of innovations through publications or industry experience.
  • Minimum of 6 years of experience in machine learning, with specific expertise in Large Language Models and Mixture of Experts.
  • Strong programming skills in Python and machine learning frameworks like TensorFlow and/or PyTorch.
  • Demonstrated ability to lead complex projects and work collaboratively in a team environment.
  • Excellent problem-solving skills and a passion for innovation.
Preferred Skills:
  • Experience with cloud computing services (AWS, Azure, GCP).
  • Knowledge of Big Data technologies (Hadoop, Spark).
  • Familiarity with containerization and orchestration technologies (Docker, Kubernetes).
  • Publications or presentations in recognized Machine Learning journals or conferences.
We at webAI are committed to living out the core values we have put in place as the foundation on which we operate as a team. We seek individuals who exemplify the following:
  • Truth - Emphasizing transparency and honesty in every interaction and decision.
  • Ownership - Taking full responsibility for one's actions and decisions, demonstrating commitment to the success of our clients.
  • Tenacity - Persisting in the face of challenges and setbacks, continually striving for excellence and improvement.
  • Humility - Maintaining a respectful and learning-oriented mindset, acknowledging the strengths and contributions of others.
Benefits:
  • Competitive salary and performance-based incentives.
  • Comprehensive health, dental, and vision benefits package.
  • $200/mos Health and Wellness Stipend
  • $400/year Continuing Education Credit
  • Flexible work week
  • Free parking, for in-office employees
  • Unlimited Approved PTO
  • Parental, Bereavement Leave
  • Supplemental Life Insurance


webAI is an Equal Opportunity Employer and does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of webAI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works.

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