Lead Machine Learning Scientist
Updated on 3/24/2024
Humane

201-500 employees

Hardware & software built for humans
Company Overview
Humane™ stands out as a leader in the tech industry due to its commitment to creating technology that enhances the human experience, fostering a culture that values trust, joy, and meaningful interactions. The company's unique approach to integrating technology and human interaction is evident in their AI Pin, which debuted at Paris Fashion Week, demonstrating their ability to merge fashion and technology seamlessly. This blend of technical prowess and human-centric design positions Humane™ as a competitive player in the industry, offering a distinct and appealing workplace for those passionate about shaping the future of human-computer interaction.
Consulting

Company Stage

Series C

Total Funding

$241.3M

Founded

2017

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

13%

1 year growth

43%

2 year growth

140%
Locations
San Francisco, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Data Structures & Algorithms
CategoriesNew
AI & Machine Learning
Applied Machine Learning
AI Research
Requirements
  • PhD in CS, ECE, BME, or related fields with 6+ years of industry experience, or a Master’s degree with 9+ years of industry experience.
  • Expertise in algorithm design for classification, filtering, signal processing, or control.
  • Solid understanding and practical experience with machine learning methodologies.
  • Hands-on experience in taking machine learning-driven products from concept to market.
  • Proficient in one prototyping language, e.g. Python.
Responsibilities
  • Design and implement algorithms for health sensing applications using deep learning and machine learning.
  • Lead the algorithmic aspect of the product from prototyping to production phases, ensuring robustness and scalability.
  • Analyze complex datasets to extract actionable insights and inform algorithm development.
  • Identify emerging technologies that will unlock new user experiences and features.
  • Collaborate with cross-functional teams to ensure seamless integration of algorithms into product offerings.
  • Contribute and refine the product roadmap with cross functional partners.