Full-Time

Pre-Sales Machine Learning Engineer

Customer Success, US, Remote

Posted on 4/19/2024

Weight & Biases

Weight & Biases

201-500 employees

MLOps platform for managing ML experiments

Data & Analytics

Junior

Remote in USA

Required Skills
Microsoft Azure
Python
Tensorflow
Keras
Pytorch
AWS
Linux/Unix
Google Cloud Platform
Requirements
  • 2-3 years of relevant experience in a similar role
  • Experience using TensorFlow/Keras, PyTorch Lightning
  • Strong programming proficiency in Python
  • Excellent communication and presentation skills
  • Experience with cloud platforms (AWS, GCP, Azure)
  • Experience with Linux/Unix
Responsibilities
  • Implementing effective machine learning pipelines using Weights & Biases tools
  • Partnering with customers to evaluate W&B in solving their problems
  • Articulating W&B product best practices
  • Providing product demos and workshops
  • Creating processes for the pre-sales lifecycle
  • Collaborating with internal teams to influence product roadmap

Weights & Biases provides a robust MLOps platform essential for machine learning practitioners focused on optimizing and managing their ML experiments. It is an attractive workplace due to its supportive environment for collaboration and continuous learning, along with integrating cutting-edge technologies in machine learning like TensorFlow and PyTorch. The company's commitment to empowering developers by simplifying complex ML workflows establishes its position as a leader in the rapidly evolving field of machine learning operations.

Company Stage

Series C

Total Funding

$250M

Headquarters

San Francisco, California

Founded

2017

Growth & Insights
Headcount

6 month growth

1%

1 year growth

4%

2 year growth

53%

Benefits

🏝️ Unlimited vacation time

🩺 100% Medical, Dental, and Vision for employees and Family Coverage

🏠 Remote first culture with in-office flexibility in San Francisco

💵 $1000 home office budget with new high-powered laptop

🥇 Truly competitive salary and equity

🚼 12 weeks of Parental leave

📈 401(k)