Machine Learning Researcher

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Gray Swan

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

🤖 Artificial Intelligence

🔒 Cybersecurity

☁️ SaaS

Artificial Intelligence • Cybersecurity • SaaS

Gray Swan is an AI security company that builds a research-backed platform to protect AI deployments across the entire lifecycle, offering input/output filtering, continuous monitoring, automated vulnerability testing, and enterprise-focused red-teaming services. The company combines frontier research, benchmarks, and large-scale red-team competitions to discover emerging attacks and deliver adaptive, integrable protections for AI agents, models, and connected tools. Gray Swan’s products and services are aimed at enterprises, AI labs, and security researchers seeking pre-deployment assessments, post-deployment monitoring, and compliance-ready defenses.

📋 Description

• Design and develop novel ML approaches to adversarial testing, model evaluation, and robust inference. • Build and deploy ML models that meet real-world performance and scalability requirements. • Design experiments, analyze results empirically, and communicate findings through publications and internal research reports. • Develop and advance methodologies for controlling, monitoring, and analyzing ML models in production environments. • Translate research ideas into scalable AI systems deployed in real-world, adversarial settings. • Work closely with cross-functional teams to ensure research outcomes inform production systems.

🎯 Requirements

• Bachelor's degree in Computer Science, Machine Learning, Engineering, or a related technical field. • A Master's or PhD in a relevant technical field is strongly preferred, especially with a focus on machine learning and AI safety. • Experience building and deploying ML models and systems. • Demonstrated expertise in designing, training, and deploying deep learning models, particularly with PyTorch. • Strong Python programming skills; C++ preferred. • Experience developing scalable ML pipelines and integrating with cloud infrastructure (AWS, GCP, or Azure). • ML research experience: building research prototype systems, designing experiments, empirical analysis of results, and communicating results via publications. • Neural network architectures, including transformers, sequence models, and other state-of-the-art approaches. • Strong algorithmic problem-solving skills and knowledge of ML theory and optimization. • Data preprocessing, transformation, and handling large-scale, multi-modal datasets.

🏖️ Benefits

• 401k with up to 4% matching • 28 days annual leave (vacation + holidays) • Health, dental, and vision coverage • Catered lunches (Pittsburgh office) • Flexible work arrangements • Visa sponsorship available for exceptional candidates