Staff Machine Learning Engineer
Confirmed live in the last 24 hours
Hive

201-500 employees

Cloud-based AI entreprise solution software
Company Overview
Hive’s mission is to use AI to unlock the next wave of intelligent automation. The company has an industry-leading portfolio of pre-trained models that allow companies of any size to access best-in-class AI solutions at a fraction of the cost and time it would take to build them internally.
AI & Machine Learning

Company Stage

Series D

Total Funding

$175.7M

Founded

2013

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

11%

1 year growth

57%

2 year growth

77%
Locations
San Francisco, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Tensorflow
Data Structures & Algorithms
Pytorch
Natural Language Processing (NLP)
Computer Vision
CategoriesNew
AI & Machine Learning
Applied Machine Learning
Deep Learning
AI Research
Requirements
  • Bachelor's Degree in computer science or a related field
  • 8+ years of experience building web applications
  • Experience implementing highly-available distributed systems/microservices
  • Delivered scalable backend APIs
  • Strong interpersonal and communication skills
  • Experience writing code and training across distributed systems
  • Expertise in machine learning frameworks (PyTorch or Tensorflow)
  • Expertise in scripting languages (Python and/or shell scripts)
  • Subject matter expertise in at least one focus area of machine learning (computer vision or natural language processing)
Responsibilities
  • Designing and coding up the neural network
  • Gathering and refining data
  • Training and tuning the model
  • Deploying the model at scale with high throughput and uptime
  • Analyzing the results to continuously update and improve accuracy and speed
  • Writing and maintaining scalable, performant code
  • Contributing to product and core backend systems improvements
  • Improving engineering standards, tooling, and processes
  • Developing novel, accurate, and performant ML algorithms
  • Conducting metric-driven research experiments
  • Providing mentorship and onboarding for ML engineers
  • Leading cross-functional collaboration with other teams
  • Contributing to defining strategic direction and planning the roadmap
  • Maintaining awareness of industry best practices for data maintenance handling
  • Adhering to policies, guidelines, and procedures for information asset protection
  • Reporting security and policy violations/breaches to an appropriate authority