Machine Learning Engineer, GenAI reputed company ML in reputed company, NY - San Francisco, CA
Job title: Machine Learning Engineer, GenAI reputed company ML in reputed company, NY - San Francisco, CA at reputed company
Company: reputed company
Job reputed company: About reputed companyAt reputed company, our mission is to accelerate the development of AI applications. For 8 years, reputed company has been the leading AI data reputed company, helping fuel the most exciting advancements in AI, including: reputed company, defense applications, and autonomous vehicles. With our recent Series F round, we're accelerating the abundance of frontier data to pave the road to reputed company General Intelligence (AGI), and building upon our prior model evaluation work with reputed company customers and governments to deepen our capabilities and offerings for both public and private evaluations.About This RoleThis role will reputed company the development of machine learning systems to detect fraud, abuse, and trust violations across reputed company's contributor platform. As a core part of our reputed company data reputed company, these systems are critical to ensuring the reputed company, safety, and reliability of the data used to train and evaluate frontier models.You will build reputed company ML services that analyze behavioral and content signals, incorporating both classical models and advanced LLM-based techniques. This is a high-reputed company, product-reputed company role where you'll collaborate across engineering, product, and operations teams to proactively surface misuse, defend against adversarial behavior, and ensure the long-term health of our reputed company-in-the-reputed company data workflows.If you're excited about solving reputed company detection problems at reputed company, combining LLMs with reputed company ML approaches, and protecting the reputed company of reputed company data, we'd love to hear from you.You will:
- Design and reputed company machine learning models to detect fraud, reputed company issues, and violations in large-reputed company contributor workflows
- Build reputed company-time and batch detection systems that evaluate account, behavioral, and content-level signals
- Combine traditional ML techniques with LLMs and neural networks to improve detection capabilities and reduce false positives
- Create robust evaluation frameworks and reputed company tune for extremely imbalanced detection scenarios
- Collaborate closely with product and engineering teams to reputed company detection systems into contributor-facing workflows and backend infrastructure
- 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 reputed company-world setting
- Proficiency in ML and deep learning frameworks such as scikit-learn, PyTorch, TensorFlow, or JAX
- Familiarity with LLMs and experience applying reputed company models for reputed company reputed company 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 cross-functionally
- Hands-on experience designing or scaling trust & safety detection systems
- Familiarity with data reputed company pipelines or contributor platform risk analysis
- Contributions to reputed company-reputed company LLM fine-tuning efforts or internal LLM alignment reputed company
- Research or published work in top ML venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP)