Machine Learning Engineer

4 Months ago • All levels • $224,400 PA - $293,250 PA

Research Development

Job Description

As a Machine Learning Engineer at Scale, you will apply computer vision, deep learning, deep reinforcement learning, or natural language processing to enhance Scale's products and customer experience. You will utilize massive datasets to improve existing models and develop new ones. Responsibilities include taking state-of-the-art models into production, identifying areas for improvement, and building a scalable ML platform. The role involves collaborating with product and research teams to identify opportunities and applying machine learning techniques. You must be willing to multitask and learn new technologies quickly.

Good To Have:

Graduate degree in Computer Science, ML, or AI.
Experience with cloud technology stack (AWS or GCP).
Experience with generative AI models.

Must Have:

Experience with computer vision, deep learning, or NLP in production.
Solid background in algorithms, data structures, and OOP.
Strong programming skills in Python or Javascript.

Add these skills to join the top 1% applicants for this job

data-structures

aws

pytorch

deep-learning

reinforcement-learning

computer-vision

python

algorithms

tensorflow

javascript

machine-learning

The goal of a Machine Learning Engineer at Scale is to bring techniques in the fields of computer vision, deep learning and deep reinforcement learning, or natural language processing into a production environment to improve Scale's products and customer experience. Our research engineers take advantage of our unique access to massive datasets to deliver improvements to our customers.

We are building a large hybrid human-machine system in service of ML pipelines for Federal Government customers. We currently complete millions of tasks a month, and will grow to complete billions of tasks monthly.

You will:

Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.
Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics
Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines
Work with massive datasets to develop both generic models as well as fine tune models for specific products
Build the scalable ML platform to automate our ML service
Be a representative for how to apply machine learning and related techniques throughout the engineering and product organization
Be able, and willing, to multi-task and learn new technologies quickly
This role will require an active security clearance or the ability to obtain a security clearance.

Ideally You’d Have:

Extensive experience using computer vision, deep learning and deep reinforcement Learning, or natural language processing in a production environment
Solid background in algorithms, data structures, and object-oriented programming
Strong programing skills in Python or Javascript, experience in Tensorflow or PyTorch

Nice to Haves:

Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
Experience with generative AI models