Machine Learning Engineer, Federal

San Francisco, CA; New York, NY; Washington, DC

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.

You will:

1. Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.
2. Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics.
3. Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines.
4. Work with massive datasets to develop both generic models as well as fine-tune models for specific products.
5. Build the scalable ML platform to automate our ML service.
6. Be a representative for how to apply machine learning and related techniques throughout the engineering and product organization.
7. 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, deep reinforcement learning, or natural language processing in a production environment.
• Solid background in algorithms, data structures, and object-oriented programming.

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.

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.

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 of Washington DC, Texas, Colorado is:

$201,960 - $263,925 USD

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 organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We 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 affirmative action employer and 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.