Machine Learning (ML) Applied Scientist

An Machine Learning (ML) Applied Scientist is an applied research scientist of ML models.

• Context:
  • They can (typically) work on Novel ML Models, such as (currently) Transformer-based Models.
  • ...
• See: ML Engineer.

---

---

References

2023

• chat
  • Applied ML Research Scientists: They focus on developing machine learning algorithms and techniques tailored to address specific problems in clinical trials. Their success criteria include the ability to create innovative and effective models, the impact of their research on the company's products, and the improvements in the efficiency or accuracy of clinical trial processes.
  • ML Engineers: They are responsible for implementing, optimizing, and deploying ML models in the clinical trial SaaS platform. Their success criteria include the efficiency and scalability of the models, the quality of the code they produce, and the seamless integration of these models into the company's existing infrastructure.

2023

• "Machine Learning Researcher - PhD (2023)" @ Figma
  • QUOTE: ... We’re looking for engineers with a background in machine learning & artificial intelligence to improve our products and build new capabilities. You'll be driving fundamental and applied research in this area. You’ll be combining industry best practices and a first-principles approach to design and build ML models and infrastructure that will improve Figma’s design and collaboration tool.
  • What you’ll do ...:
    1. Drive fundamental and applied research in ML/AI, with Figma product use cases in mind
    2. Formulate and implement new modeling approaches both to improve the effectiveness of Figma’s current models as well as enable the launch of entirely new AI-powered product features
    3. Work in concert with other ML researchers, as well as product and infrastructure engineers to productionize new models and systems to power features in Figma’s design and collaboration tool
    4. Explore the boundaries of what is possible with the current technology set and experiment with novel ideas
  • We'd love to hear from you if you have:
    1. Recently obtained a PhD or equivalent experience in an industry research role in AI, Computer Science or a related field
    2. Demonstrated expertise in machine learning with publication record in relevant conferences, or a track record in applying machine learning techniques to products
    3. Experience in Python and machine learning frameworks (such as PyTorch, TensorFlow)
    4. Experience building systems based on deep learning, natural language processing, computer vision, and/or generative models
    5. Experience solving sophisticated problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward
    6. Experience communicating and working across functions to drive solutions.

---