Machine Learning Engineer, Federal - Scale AI : Job Details

The goal of a Machine Learning Engineer at Scale is to bring techniques in the fields of computer vision, deep learning, 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.

• 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.

• Extensive experience using computer vision, deep learning, deep reinforcement learning, or natural language processing in a production environment.

• Solid background in algorithms, data structures, and object-oriented programming.

• Strong programming skills in Python or Javascript, experience in Tensorflow or PyTorch.

• Graduate degree in Computer Science, Machine Learning, or Artificial Intelligence specialization.

• Experience working with cloud technology stack (e.g., AWS or GCP) and developing machine learning models in a cloud environment.

• Experience with generative AI models.