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
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $224,400 - $293,250 USD Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations
