Scale AI, Inc.
Manager, Machine Learning Research Engineer, Generative AI
Scale AI, Inc., San Francisco, California, United States, 94199
Scale's Generative AI Data Engine powers the most advanced LLMs and generative models in the world through RLHF/RLAIF, data generation, model evaluation, safety, and alignment.
As the Manager of the Generative AI Applied ML team, you will lead a talented team of research engineers and ML engineers focused on delivering scalable, production-ready solutions to support Scale's GenAI Data Engine, such as rater-assistant models, LLM as a judge, critique modeling, fraud and cheating detection, etc. This role is critical for designing and executing a roadmap that accelerates our frontier model building customers' Generative AI initiatives forward. We are looking for someone with a strong background and hands-on experience in fine-tuning and evaluating LLMs, prioritizing practical, production-oriented problem-solving over academic research. This position requires a deep commitment to building robust, efficient systems that meet the demands of large-scale production, supporting millions of tasks monthly across a hybrid human-machine system, with the aim to scale into billions monthly.
This is a unique opportunity to drive impactful, production-focused work on the frontier of AI, collaborating with industry-leading professionals to shape and deliver reliable, high-performance solutions for real-world applications.
You will:Manage a team of highly effective research engineers and ML engineers. Provide guidance, mentorship, and technical leadership to a team of researchers and engineers working on Generative AI projects.Develop and evaluate methods for integrating machine learning into human-in-the-loop labeling systems to ensure high-quality and throughput labels for our customers.Implement and improve on state-of-the-art research developed internally and from the community and put them into production to solve problems for our customers and taskers.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 a scalable autorating platform that will improve quality and efficiency of the generative AI data engine.Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.Must be able to commute to the San Francisco Office 1-2x weekly.
Ideally you'd have:7+ years of full time work experience in deep learning, deep reinforcement learning, or natural language processing in a production environment, especially post-training experience with LLMs.Experience managing a 5+ people team or leading a technical workstream.Strong programming skills in Python, experience in PyTorch or Tensorflow.Experience with MLOps and the automation of model training & evaluation.Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.Deep appreciation for building high-quality, robust, reusable productionized ML systems.
Nice to haves:Publication experience in the field or related topics.Experience with using LLMs as a judge for AutoRating systems.Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization.
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 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.
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.
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As the Manager of the Generative AI Applied ML team, you will lead a talented team of research engineers and ML engineers focused on delivering scalable, production-ready solutions to support Scale's GenAI Data Engine, such as rater-assistant models, LLM as a judge, critique modeling, fraud and cheating detection, etc. This role is critical for designing and executing a roadmap that accelerates our frontier model building customers' Generative AI initiatives forward. We are looking for someone with a strong background and hands-on experience in fine-tuning and evaluating LLMs, prioritizing practical, production-oriented problem-solving over academic research. This position requires a deep commitment to building robust, efficient systems that meet the demands of large-scale production, supporting millions of tasks monthly across a hybrid human-machine system, with the aim to scale into billions monthly.
This is a unique opportunity to drive impactful, production-focused work on the frontier of AI, collaborating with industry-leading professionals to shape and deliver reliable, high-performance solutions for real-world applications.
You will:Manage a team of highly effective research engineers and ML engineers. Provide guidance, mentorship, and technical leadership to a team of researchers and engineers working on Generative AI projects.Develop and evaluate methods for integrating machine learning into human-in-the-loop labeling systems to ensure high-quality and throughput labels for our customers.Implement and improve on state-of-the-art research developed internally and from the community and put them into production to solve problems for our customers and taskers.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 a scalable autorating platform that will improve quality and efficiency of the generative AI data engine.Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.Must be able to commute to the San Francisco Office 1-2x weekly.
Ideally you'd have:7+ years of full time work experience in deep learning, deep reinforcement learning, or natural language processing in a production environment, especially post-training experience with LLMs.Experience managing a 5+ people team or leading a technical workstream.Strong programming skills in Python, experience in PyTorch or Tensorflow.Experience with MLOps and the automation of model training & evaluation.Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.Deep appreciation for building high-quality, robust, reusable productionized ML systems.
Nice to haves:Publication experience in the field or related topics.Experience with using LLMs as a judge for AutoRating systems.Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization.
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 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.
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.
#J-18808-Ljbffr