Senior Machine Learning Engineer

3 weeks ago

Austin, Texas, United States webAI Full time

About webAI:

webAI is a software company that is revolutionizing the field of artificial intelligence by developing a decentralized AI development platform. Our technology enables the creation of powerful AI models using limited amounts of data, challenging the conventional wisdom that big data is the key to unlocking AI's full potential.

At webAI, we foster a dynamic and fast-growing team that values a fun and growth-oriented office culture. We are committed to living out our core values, which serve as the foundation for our team's operations.

We seek individuals who embody the following traits:

  • Truth - Emphasizing transparency and honesty in every interaction and decision.
  • Ownership - Taking full responsibility for one's actions and decisions, demonstrating commitment to our clients' success.
  • 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.

The Role:

We are seeking a Senior Machine Learning Engineer with expertise in Large Language Models (LLMs) and Natural Language Processing (NLP) to join our innovative team. This role will focus on developing and deploying state-of-the-art NLP models that power webAI's platform.

If you have experience working with transformer models, language generation, and advanced text analytics, this is an excellent opportunity to apply your skills on groundbreaking AI technology.

You will collaborate closely with our research and engineering teams to design, build, and optimize models that work with both structured and unstructured language data.

Key Responsibilities:

  • Design, build, and fine-tune LLMs and NLP models (e.g., GPT, BERT) for tasks like language understanding and generation.
  • Extend webAI's existing LLM frameworks and libraries, incorporating the latest research in language models.
  • Preprocess and prepare text datasets for training, including tokenization and feature extraction.
  • Implement MLOps best practices for deploying scalable, production-level models on cloud platforms.
  • Collaborate with cross-functional teams to integrate LLM models into the webAI platform.
  • Stay updated on LLM advancements and apply the latest research to improve model performance.

Requirements:

  • 5+ years of experience in machine learning, with a focus on NLP and LLMs.
  • Bachelor's (Master's preferred) in Computer Science, Machine Learning, or related field.
  • Expertise in transformer architectures (e.g., GPT, BERT), text preprocessing, and feature engineering.
  • Proficiency in Python and NLP libraries (Hugging Face, TensorFlow, PyTorch).
  • Experience with MLOps tools (MLFlow, Kubeflow, etc.).
  • Strong communication skills and passion for learning.

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 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, political affiliation, 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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