Job Description
About Scale
- Mission: Accelerate AI application development.
- 8 years leading AI data foundry.
- Focus areas: Generative AI, Defense, Autonomous Vehicles.
- Recent round: Series F funding.
- Goal: Enable frontier data, support AGI development, improve evaluation capabilities.
About This Role
- Lead the development of ML systems for detecting fraud, abuse, and trust violations.
- Ensure data quality, safety, and reliability in training frontier models.
- Build scalable ML services analyzing behavioral and content signals.
- Use classical models and advanced LLM-based techniques.
- Collaborate across engineering, product, and operations teams.
- Protect AI training data integrity.
Responsibilities
- Design and deploy ML models for fraud, quality issues, violations.
- Build real-time and batch detection systems.
- Combine traditional ML with LLMs and neural networks.
- Create evaluation frameworks for imbalanced scenarios.
- Integrate detection systems into workflows.
Qualifications
- 3+ years of experience deploying ML models.
- Experience in trust & safety, fraud detection, adversarial modeling.
- Proficiency in scikit-learn, PyTorch, TensorFlow, JAX.
- Familiarity with LLMs for structured downstream tasks.
- Strong software engineering in microservice architectures (AWS/GCP).
- Excellent cross-functional communication.
Nice to Have
- Experience scaling trust & safety detection.
- Knowledge of data quality pipelines / risk analysis.
- Contributions to open-source LLM efforts.
- Research publications in top ML venues.
Compensation & Benefits
- Salary range: $176,000—$220,000 USD.
- Additional benefits: Health, dental, vision, retirement, stipends, PTO.
- Equity may be granted.
- Policy: 90-day wait before reapplying for same role.
About Us
- Transforming industries with AI.
- Powering top LLMs and models.
- Clients include OpenAI, Meta, Microsoft, U.S. Army, GM.
- Equal opportunity employer.
- Contact for accommodations.
- Privacy policy applies.
Job Highlights
Qualifications
- 3+ years ML experience.
- Expertise in trust & safety, fraud, abuse prevention.
- Proficiency in ML frameworks.
- Familiarity with LLMs.
- Software engineering skills in microservices.
- Communication skills.
- Experience in detection system scaling.
- Knowledge in data quality pipelines.
- Open-source or research publications.
Benefits
- Salary, equity, benefits.
- Salary depends on location, skills, experience.
- Health, vision, dental, retirement, stipends.
- USD 176,000—$220,000.
Responsibilities
- Leading ML system development.
- Ensuring data quality and safety.
- Building scalable detection services.
- Collaborating with teams.
- Protecting training data integrity.