Machine Learning Engineer, Violations

Company:  Scale AI
Location: San Francisco
Closing Date: 16/10/2024
Salary: £250 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

About Job

At Scale, our Generative AI Data Engine powers the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment.

We’re looking for Machine Learning Engineers to join our team. In this role, you'll be given the opportunity to build cutting-edge models to make an impact in the AI industry and meaningfully drive millions of dollars in revenue. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

The ideal person is a natural entrepreneurial engineer who can take an ambiguous scope and lead the execution of outcomes, doing what it takes to hit them incl coding, defining requirements, proposing solutions, etc. We strongly believe the best engineers own outcomes and deeply understand customer problems.

Tweet by Greg Brockman

You’re excited about solving customer problems, and you pick the technologies and tactics that balance speed, function, and long-term robustness.

You will:

  • Develop state-of-the-art models to detect and combat fraud, cheating, and spamming in the GenAI ecosystem. Your work will play a crucial role in maintaining the trust and reliability of our AI solutions.
  • Design and implement features that elevate model performance, ensuring our solutions stay ahead of emerging threats and challenges.
  • Define and drive key performance indicators that directly influence business success.
  • Assess technical tradeoffs with a critical eye, making decisions that balance innovation, efficiency, and practicality.
  • Uphold coding standards and architectural principles by crafting clean, well-documented, and modular code.
  • Actively engage in code reviews, offering constructive feedback, and actively contributing to continuous improvement efforts across the engineering department.

Ideally you'd have:

  • Strong understanding of machine learning approaches and algorithms
  • Able to build out ML pipeline from feature generation to model deployment
  • Able to prioritize duties and work well on your own
  • Ability to work with both internal and external partners
  • Skilled at solving open ambiguous problems
  • Strong collaboration skills

Nice to haves:

  • Have experience with AI platforms and technologies, including generative models and LLMs.
  • Experience building ML infrastructure.

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