Machine Learning Engineer, Numbers Station
$125-175k
+ Equity
Office located in Menlo Park, CA
AI data workflow automation
Job no longer available
AI data workflow automation
1-20 employees
Job no longer available
$125-175k
+ Equity
Office located in Menlo Park, CA
1-20 employees
Company mission
To enable data practitioners of all skill levels to rapidly automate workflows in the modern data stack using natural language.
Role
Who you are
- 3+ years of professional experience with machine learning, or 1+ years of professional experience with machine learning with an advanced degree in a relevant field
- Expertise in modern machine learning frameworks and technologies (e.g. PyTorch, TensorFlow, transformers), and an obsession with thorough ML evaluation
- Strong coding skills and knowledge of ML techniques and algorithms
- Ability to work in a fast-paced environment and navigate ambiguity
- Strong technical communication skills
- Self-motivation, positive attitude, and a growth mindset
Desirable
- Experience using and developing with foundation models
- Experience working directly with customers on machine learning problems
- Experience building and maintaining large scale, production data pipelines for machine learning applications
What the job involves
- As a Machine Learning Engineer, you'll engage new ML use cases through hands-on customer problems and generalize learnings into the core Numbers Station platform
- With a combination of strong programming skills and a user-focused mindset, you will have full ownership and responsibility for building, shipping, and maintaining innovative new functionality across the stack
- Improve accuracy of our production machine learning systems by applying the latest published research and your own creative solutions, including but not limited to prompt tuning, and guarding against hallucinations
- Own end-to-end accuracy and performance for our machine learning solutions
- Stay up to date on the latest research publications, and rapidly assess the latest results for production and scalability potential
- Work closely with product leadership and customers on training datasets and error analysis
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Company
Funding (last 2 of 3 rounds)
Mar 2023
$12.5m
SERIES A
Aug 2022
$5m
SEED
Total funding: $22.5m
Our take
Data teams face a difficult task, with the data they need for their analytical work entered messily, located incorrectly or stuck in disconnected silos around the business. Before they are able to begin to work with data it has to be cleaned and reorganized manually, wasting vast amounts of time and resources. Enter Numbers Station, an AI-powered data stack automation tool which uses the latest developments in AI to clean and organize a company's data in a fraction of the time.
At a time when a lot of AI talent is focusing on content generation, Numbers Station is virtually alone in applying the technology to data cleaning, where the problems are just as difficult to solve even if they can't create exciting headlines. This means it's in a strong position to build a market-leading company in this space while helping its customers make better use of their data.
Funding will allow the company to further develop its product and hire additional talent. In the longer term, the company intends to move beyond data preparation to data analysis, allowing it to grow into an essential component in the data stacks of future enterprises.
Steph
Company Specialist at Welcome to the Jungle