About the role:
The Samsara AI team builds end-to-end machine learning and computer vision
solutions for our customers as well as core ML infrastructure for Samsara. As
a Senior Data Scientist you will be a science leader and key contributor in
building core models and predictive techniques for use in building and
understanding products. You will work closely with other scientists as well as
full-stack, firmware, and platform teams to deliver core infrastructure,
services, and optimizations.
This role can be office-based or fully remote in the US and Canada.
In this role, you will:
- Build and improve the accuracy of ML / CV models, including retraining and optimizing open-source models to solve Samsara-specific problems
- Work with petabyte-scale data from Samsara camera and sensor devices to develop new models
- Lead org-wide initiatives on science, testing, and data-driven decision making
- Research, adapt, and apply cutting edge techniques in CV and deep learning
- Optimize models for inference on the backend and/or on edge devices
- Partner with our hardware teams to design devices for optimal performance and cost
- Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs.
- Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices
Minimum requirements for the role:
- BS or MS in Computer Science or other quantitative field (e.g., Applied Math, Statistics)
- 8+ years experience as a Data Scientist, Machine Learning Engineer, or similar role
- Proficiency in data modeling as well as SQL, Python, R, or a similar scripting language
- Ability to distill informal or ambiguous customer and business requirements into crisp problem definitions
- Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge
- Experience coaching and mentoring more junior scientists
An ideal candidate also has:
- PhD in Computer Science or quantitative discipline (e.g., Applied Math, Physics, Statistics)
- Strong functional knowledge of common tools like Jupyter Notebooks, AWS (e.g., EMR, Redshift, S3, Sagemaker)
- Record of successful mentoring and development of junior team members
- Experience working with large datasets using distributed computing (e.g., Spark, Hive)