Senior Machine Learning Engineer
Posted on 7/19/2023
INACTIVE
Kiva

201-500 employees

Perfect Food Company
Company Overview
Kiva envisions a financially inclusive world where all people hold the power to improve their lives.
Consumer Goods

Company Stage

Seed

Total Funding

$13.5M

Founded

2005

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-4%
Locations
Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Kotlin
Kubernetes
Python
Airflow
SQL
Apache Kafka
Java
Docker
Natural Language Processing (NLP)
CategoriesNew
AI & Machine Learning
DevOps & Infrastructure
Software Engineering
Requirements
  • Work to create impactful and sustainable solutions to complex problems by taking bold and measured risks
  • Balance your technical excellence with a high E.Q., showing up with a sense of empathy, awareness, and responsibility
  • Share the knowledge you bring and gain generously with your peers to perpetuate a culture of engineering excellence
  • You have a BS in a quantitative discipline (computer science, engineering, physics, mathematics, or a related field) or comparable work experience
  • You have 3+ years of experience in prototyping and productionizing data and machine learning-driven products
  • You have experience in one or more of the following - recommender systems, predictive modeling, reinforcement learning (e.g., multi-armed bandits), personalized search, computational optimization, natural language processing, deep learning, causal inference especially as applied to e-commerce/marketplaces/email marketing
  • You have experience with Docker, Kubernetes, and workflow orchestration tools (e.g. Airflow)
  • You have coding skills in Python and SQL (nice to have Kotlin or Java experience)
  • You have exposure to distributed systems and architectures (such as Kafka)
  • You have the ability to communicate findings and recommendations to technical and non-technical audiences
  • You are willing to learn, take initiative, and wear multiple hats as required
Responsibilities
  • Help solve a variety of problems using data to influence the experience of millions of lenders and borrowers around the world
  • Ideate, prototype, and productionize machine learning models
  • Build and scale production-ready ML and back-end infrastructure and services
  • Influence and help execute our product strategy by collaborating with product managers, business stakeholders as well as other engineers
  • Help foster a spirit of innovation and collaboration both within the team and across the organization