Scale AI, Inc.
Machine Learning Engineer, Federal
Scale AI, Inc., San Francisco, California, United States, 94199
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 programming 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 (e.g. AWS or GCP) and developing machine learning models in a cloud environment.
Experience with generative AI models.
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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 programming 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 (e.g. AWS or GCP) and developing machine learning models in a cloud environment.
Experience with generative AI models.
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