Machine Learning Engineer, Violations at Scale AI
San Francisco, CA
About the Job
About ScaleAt Scale AI, our mission is to accelerate the development of AI applications
For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles
With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.About Data EngineOur Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment
The data we are producing is some of the most important work for how humanity will interact with AI.About our Fraud teamThe Fraud team works on preventing violations to our terms and service
They protect our platform against potential fraud, cheating, and abuse that are emerging in the GenAI era
The team works at the intersection of machine learning, analytics, and security
We’re looking for Machine Learning Engineers to join this team
In this role, you'll be given the opportunity to build cutting-edge models to make an impact in the AI industry, and meaningfully drive millions of dollars in revenue
You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.Responsibilities:Develop state-of-the-art models to detect and combat fraud, cheating, and spamming in the GenAI ecosystem
Your work will play a crucial role in maintaining the trust and reliability of our AI solutions.Design and implement features that elevate model performance, ensuring our solutions stay ahead of emerging threats and challenges.Define and drive key performance indicators that directly influence business success.Assess technical tradeoffs with a critical eye, making decisions that balance innovation, efficiency, and practicality.Uphold coding standards and architectural principles by crafting clean, well-documented, and modular code.Actively engage in code reviews, offering constructive feedback, and actively contributing to continuous improvement efforts across the engineering department.Requirements:Strong understanding of machine learning approaches and algorithmsAble to build out ML pipeline from feature generation to model deploymentAble to prioritize duties and work well on your ownAbility to work with both internal and external partnersSkilled at solving open ambiguous problemsStrong collaboration skillsCompensation 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:$176,000—$220,000 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role
This allows us to ensure a fair and thorough evaluation of all applicants.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. 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
Please see the United States Department of Labor's Know Your Rights poster for additional information.We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates
We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws
Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data
Please see our privacy policy for additional information.
For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles
With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.About Data EngineOur Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment
The data we are producing is some of the most important work for how humanity will interact with AI.About our Fraud teamThe Fraud team works on preventing violations to our terms and service
They protect our platform against potential fraud, cheating, and abuse that are emerging in the GenAI era
The team works at the intersection of machine learning, analytics, and security
We’re looking for Machine Learning Engineers to join this team
In this role, you'll be given the opportunity to build cutting-edge models to make an impact in the AI industry, and meaningfully drive millions of dollars in revenue
You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.Responsibilities:Develop state-of-the-art models to detect and combat fraud, cheating, and spamming in the GenAI ecosystem
Your work will play a crucial role in maintaining the trust and reliability of our AI solutions.Design and implement features that elevate model performance, ensuring our solutions stay ahead of emerging threats and challenges.Define and drive key performance indicators that directly influence business success.Assess technical tradeoffs with a critical eye, making decisions that balance innovation, efficiency, and practicality.Uphold coding standards and architectural principles by crafting clean, well-documented, and modular code.Actively engage in code reviews, offering constructive feedback, and actively contributing to continuous improvement efforts across the engineering department.Requirements:Strong understanding of machine learning approaches and algorithmsAble to build out ML pipeline from feature generation to model deploymentAble to prioritize duties and work well on your ownAbility to work with both internal and external partnersSkilled at solving open ambiguous problemsStrong collaboration skillsCompensation 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:$176,000—$220,000 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role
This allows us to ensure a fair and thorough evaluation of all applicants.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. 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
accommodations@scale.com
Please see the United States Department of Labor's Know Your Rights poster for additional information.We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates
We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws
Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data
Please see our privacy policy for additional information.
