Machine Learning Engineer GenAI Applied ML
Machine Learning Engineer GenAI Applied ML
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$ 176000 - 220000
1 Vacancy
Job Description
About Scale
At 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 were 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 This Role
This role will lead the development of machine learning systems to detect fraud abuse and trust violations across Scales contributor platform. As a core part of our Generative AI data engine these systems are critical to ensuring the quality safety and reliability of the data used to train and evaluate frontier models.
You will build scalable ML services that analyze behavioral and content signals incorporating both classical models and advanced LLMbased techniques. This is a highimpact productfocused role where youll collaborate across engineering product and operations teams to proactively surface misuse defend against adversarial behavior and ensure the longterm health of our humanintheloop data workflows.
If youre excited about solving complex detection problems at scale combining LLMs with structured ML approaches and protecting the integrity of AI training data wed love to hear from you.
You will:
- Design and deploy machine learning models to detect fraud quality issues and violations in largescale contributor workflows
- Build realtime and batch detection systems that evaluate account behavioral and contentlevel signals
- Combine traditional ML techniques with LLMs and neural networks to improve detection capabilities and reduce false positives
- Create robust evaluation frameworks and actively tune for extremely imbalanced detection scenarios
- Collaborate closely with product and engineering teams to embed detection systems into contributorfacing workflows and backend infrastructure
Ideally youd have:
- 3 years of experience building and deploying ML models in production environments
- Experience with trust & safety fraud detection abuse prevention or adversarial modeling in a realworld setting
- Proficiency in ML and deep learning frameworks such as scikitlearn PyTorch TensorFlow or JAX
- Familiarity with LLMs and experience applying foundation models for structured downstream tasks
- Strong software engineering fundamentals and experience building ML systems in microservice architectures (e.g. using AWS or GCP)
- Excellent communication skills and a proven ability to work crossfunctionally
Nice to have:
- Handson experience designing or scaling trust & safety detection systems
- Familiarity with data quality pipelines or contributor platform risk analysis
- Contributions to opensource LLM finetuning efforts or internal LLM alignment projects
- Research or published work in top ML venues (e.g. NeurIPS ICML ICLR ACL EMNLP)
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 jobrelated 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. Youll 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 postings subtitle for where this position will be located. For pay transparency purposes the base salary range for this fulltime position in the locations of San Francisco New York Seattle is:
$176000 $220000 USD
PLEASE NOTE:Our policy requires a 90day 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 worlds 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 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 Labors Know Your Rights poster for additional information.
We comply with the United States Department of Labors 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 for additional information.
Employment Type
Full Time
