{"id":2526748,"url":"https://alion.io/job/gray-swan-ai-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":178416,"name":"Gray Swan AI","domain":"grayswan.ai","url":"https://alion.io/company/gray-swan-ai","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pittsburgh, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":257000,"currency":"USD","period":"year","gross":null,"usd_annual":257000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C++","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"Red Teaming","optional":false},{"name":"Fine-tuning","optional":true},{"name":"Multimodal AI","optional":true},{"name":"Synthetic Data","optional":true}],"status":"live","first_seen_at":"2026-09-29T18:35:34Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-18T02:00:31Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"description":"About Gray Swan\nGray Swan is on a mission to empower the world to use AI safely and securely. We evaluate AI models for the leading frontier labs along with building real-time threat detection and adaptive adversarial red teaming agents for teams deploying AI.\nWe're a team of approximately 50 people, well-funded, growing quickly. Our work directly influences how the world deploys AI agents and systems at scale.\nLearn more about how we work.\nThe Role\nAs a Machine Learning Engineer at Gray Swan AI, you will play a pivotal role in shaping the future of AI safety solutions.\nResearch at Gray Swan AI is tightly tied to real-world impact. AI security is not a solved problem, and this role is a mix of applied research and system building: developing new approaches to adversarial testing, model evaluation, and robust inference that directly inform how secure AI systems are deployed in practice. You will work at the boundary between research and production, translating novel ideas into scalable AI systems that withstand adversarial pressure.\nYour expertise in state-of-the-art deep learning architectures, distributed systems, and parallel computing will enable you to tackle complex challenges associated with resource-intensive models. You will be responsible for advancing our methodologies for controlling, monitoring, and analyzing these models, ensuring they meet the rigorous demands of production environments.\nJoin Gray Swan AI to work alongside leading minds in AI safety and apply your technical depth to problems that genuinely matter!\nWhat You’ll Do\nLead the design, development, and deployment of advanced machine learning models to enhance system performance and scalability.\n\nTackle complex challenges associated with resource-intensive models using distributed systems and parallel computing.\n\nAdvance methodologies for controlling, monitoring, and analyzing machine learning models in production environments.\n\nDevelop new approaches to adversarial testing, model evaluation, and robust inference.\n\nTranslate research ideas into scalable AI systems deployed in real-world, adversarial settings.\n\nWork closely with cross-functional teams to ensure research outcomes inform production systems.\n\nWho You Are\nEducation\nBachelor’s degree in Computer Science, Machine Learning, Engineering, or a related technical field is required.\n\nExperience\nExperience in building and deploying machine learning models and systems.\n\nDemonstrated expertise in designing, training, and deploying deep learning models with frameworks like PyTorch.\n\nStrong programming experience in Python and C++ (preferred)\n\nPractical experience developing scalable machine learning pipelines and integrating them with cloud infrastructure (e.g., AWS, GCP, Azure).\n\nExperience conducting ML research, including building research prototype systems, experiment design, empirical analysis of results, and communicating results via publications.\n\nGood to have: experience with modern ML methods such as LLMs (training, finetuning, and/or analyzing), synthetic data generation pipelines, and AI safety or security work.\n\nCore Technical Skills\nIn-depth knowledge of neural network architectures, including sequence models, transformers, and other state-of-the-art approaches.\n\nStrong algorithmic problem-solving skills and comprehensive knowledge of ML theory and optimization techniques.\n\nProficiency in data preprocessing, transformation, and handling large-scale, multi-modal datasets.\n\nBonus Points If You Have\nExperience with AI safety practices such as model validation, robustness testing, and continuous monitoring for safety and security incidents throughout deployment.\n\nExperience with AI safety and security assessments and adversarial testing.\n\nYou’ll Thrive Here If\nYou are genuinely excited by the intersection of research and engineering, and want to both develop new AI safety ideas and see them running in real systems.\n\nYou are motivated by real-world impact and want your work to directly influence how major AI companies deploy models right now (we work with many of the leading AI labs).\n\nYou are eager to deepen your AI safety expertise by working alongside a team that includes some of the most respected and influential thinkers in the field.\n\nYou thrive in a fast-paced, dynamic startup environment where ambiguity is expected.\n\nYou bring strong collaboration and problem-solving skills, with a focus on driving meaningful, lasting impact.\n\nCompensation & Benefits\nWe offer a competitive compensation package designed to reward impact and incentivize growth. Our compensation philosophy is informed by our current valuation and recent industry data.\nSalary: $160-257k, depending on level, plus performance-based bonus and a competitive equity package\nBenefits:\n401k with up to 4% matching\n\n28 days annual leave (vacation + holidays)\n\nHealth, dental, and vision coverage\n\nCatered lunches (Pittsburgh office)\n\nFlexible work arrangements\n\nVisa sponsorship available for exceptional candidates\n\nTypical Interview Process\nApplication review. We read everything; we’ll respond within 10 days.\nRecruiter Screen. We learn about you; you learn about us.\nTechnical interview or Hiring Manager Interview.\nRole related assesment\nExperience & culture interview\nReference checks. We’ll reach out to 3-5 references that you provide.\nOffer. 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