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:
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Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.
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Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics
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Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines
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Work with massive datasets to develop both generic models as well as fine tune models for specific products
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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
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Be able, and willing, to multi-task and learn new technologies quickly
Ideally You’d Have:
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US citizenship and US Government Security Clearance is a requirement (TS/SCI preferred)
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Extensive experience using computer vision, deep learning and deep reinforcement Learning, or natural language processing in a production environment
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Solid background in algorithms, data structures, and object-oriented programming
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Strong programing skills in Python or Javascript, experience in Tensorflow or PyTorch
Nice to Haves:
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Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
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Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
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Experience with generative AI models
The base salary range for this full-time position in Washington DC, is $200,800 - $240,960. Compensation packages at Scale 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. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Scale employees are also granted Stock Options that are awarded upon board of director approval. 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.
About Us:
At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how machine learning can build innovative products. Our products provide access to human-powered data for hundreds of use cases and are used by industry leaders such as Open AI, Lyft, Meta, GM, Samsung, Airbnb, NVIDIA, and many more. We’ve recently raised $325 million in Series E funding at a valuation of $7B+ and are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodation[email protected]. Please see the United States Department of Labor’s EEO poster and EEO poster supplement for additional information.
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