1,804 Safeguards jobs in the United States

Enhance the nation's economic prosperity by safeguarding its borders.

As a Customs and Border Protection Officer , you will be part of a 60,000+ workforce that protects America's security and facilitates legitimate trade and travel.

• Enforce laws and regulations related to customs, immigration, and agriculture.
• Ensure the admissibility of individuals for entry into the United States.
• Prevent the illegal entry of individuals and prohibited goods and the smuggling of contraband.

• Citizenship: You must be a U.S. citizen.
• Residency: You must have lived in the U.S. for at least three of the last five years.
• Age Restriction: You must be referred before your 40th birthday (some exceptions apply).
• Veterans' Preference: Eligible veterans may qualify for an appointment.

Formal Training includes two-week orientation and 101-day academy at FLETC in Glynco, GA. Spanish training may be required for certain locations.

Our client's MCFR project seeks a motivated engineer to develop tools for inventory calculations and uncertainty analysis for material accounting. Your job will include identifying and quantifying new or unanticipated sources of uncertainty; developing computational tools and processes for propagating uncertainty across complex, dynamic systems; and conducting sensitivity analyses to prioritize efforts to reduce uncertainty.

Responsibilities:

• Create methodologies and tools for calculating special nuclear material inventories and uncertainties in MCFR fuel salts and waste products under varied deployment, operational, and process conditions.
• Develop approaches to identify, quantify, and propagate uncertainty from diverse sources of data and computational tools
• Develop statistical methodologies for detection of inventory losses or anomalies
• Conduct sensitivity analysis to prioritize sources of uncertainty and inform the selection, design, and testing of instrumentation used for material accounting across reactor systems
• Collaborate with cross-functional, multi-disciplinary engineering teams to develop material accounting and safeguards approaches for MCFR plants and address technical challenges
• Facilitate licensing activities for MCFR technology
• Participate in training programs and workshops to enhance understanding of safeguards and material accounting in domestic and international contexts
• Publish and present results for peer review to advance broad public acceptance

• B.S. (+4-6 years relevant experience), M.S. (+2-3 years relevant experience), or Ph.D (+1-2 years relevant experience) in mathematics, data science, engineering, physical sciences, or a related technical field, is required.
• Good working knowledge of nuclear and/or general numerical methods, e.g., partial differential equations, dynamics, deterministic and stochastic particle transport, isotopic depletion, perturbation theory, nuclear data, kinetics.
• Experience in uncertainty analysis and quantification for complex systems is required.
• Experience with nuclear engineering software such as ARMI, MCNP, OpenMC, Serpent, SCALE, DIF3D, Attila, GRIFFIN, PROTEUS, MC2, PARTISN, PARCS, APA, CASMO, DRAGON, etc. is highly desired.
• Strong programming skills in any language is required, with a strong preference for Python, C++, Git, and Github experience.
• Ability to work in a rapidly evolving and iterative design environment.
• Excellent analytical, problem-solving, and communication skills, with the ability to convey complex technical information effectively to diverse audiences.
• Proven ability to work collaboratively in cross-functional teams, prioritize tasks, and manage multiple projects simultaneously.
• The successful candidate will possess a high degree of trust and integrity, communicate openly and display respect and a desire to foster teamwork.
• Actual position starting level and title will be determined based on assessment of qualifications.

• Familiarity with domestic and international safeguards, including prior experience working on material control and accounting (MC&A) programs for advanced reactors or bulk material handling fuel cycle facilities
• Experience with advanced and/or molten salt reactor core design
• Ability and professionalism to work within published regulatory guidelines for nuclear reactor design, including experience working under an NQA-1 or equivalent quality program

• Analyze the deployment of our products and services to identify how these systems are being misused or abused, with a particular focus on influence operations
• Develop abuse signals and tracking strategies to proactively detect adversarial actors
• Study trends internally and in the broader ecosystem to anticipate how systems could be misused or manipulated for harm in the future, generating and publishing reports
• Create actionable intelligence reports on new attack vectors, vulnerabilities, and threat actor TTPs targeting LLM systems
• Utilize the results of deep dive investigations to implement systematic changes to our safety approach to mitigate harm
• Keep abreast of the latest industry risks, vulnerabilities, and issues related to the use of language models and generative AI; identify opportunities for improvement to our policies, controls, and enforcement mechanisms
• Forecast how abuse actors will leverage new advances in AI technology and inform safety by design strategies
• Build and maintain relationships with external threat intelligence partners and information sharing communities
• Work with cross-functional team members to build out our threat intelligence program, establishing processes, tools, and best practices

• Have experience in technical analysis and investigations, including skills in SQL and Python
• Have experience with large language models and a deep understanding of AI technology
• Have experience tracking bad actors in the deep and dark web.
• Have subject matter expertise in abusive user behavior detection, for example influence operations, coordinated inauthentic behavior patterns, and/or cyber threat intelligence
• Can derive insights from large amounts of data to make key decisions and recommendations
• Have experience conducting threat actor profiling and utilizing threat intelligence frameworks
• Have strong project management skills and the ability to build processes from the ground up
• Possess excellent communication skills to collaborate with cross-functional teams

• Design and build scalable ML infrastructure to support real-time and batch classifier and safety evaluations across our model ecosystem
• Build monitoring and observability tools to track model performance, data quality, and system health for safety-critical applications
• Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems
• Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards
• Implement automated testing, deployment, and rollback systems for ML models in production safety applications
• Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs
• Contribute to the development of internal tools and frameworks that accelerate safety research and deployment

• Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment
• Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX
• Have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes)
• Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads
• Have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems)
• Are results-oriented, with a bias towards reliability and impact in safety-critical systems
• Enjoy collaborating with researchers and translating cutting-edge research into production systems
• Care deeply about AI safety and the societal impacts of your work

• Working with large language models and modern transformer architectures
• Implementing A/B testing frameworks and experimentation infrastructure for ML systems
• Developing monitoring and alerting systems for ML model performance and data drift
• Building automated labeling systems and human-in-the-loop workflows
• Experience in trust & safety, fraud prevention, or content moderation domains
• Knowledge of privacy-preserving ML techniques and compliance requirements
• Contributing to open-source ML infrastructure projects

• Build machine learning models to detect unwanted or anomalous behaviors from users and API partners, and integrate them into our production system
• Improve our automated detection and enforcement systems as needed
• Analyze user reports of inappropriate accounts and build machine learning models to detect similar instances proactively
• Surface abuse patterns to our research teams to harden models at the training stage

• Have 4+ years of experience in a research/ML engineering or an applied research scientist position, preferably with a focus on AI safety.
• Have proficiency in Python, LLMs, SQL and data analysis/data mining tools.
• Have proficiency in building safe AI/ML systems, such as behavioral classifiers or anomaly detection.
• Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
• Care about the societal impacts and long-term implications of your work.

• Machine learning frameworks like Scikit-Learn, TensorFlow, or PyTorch
• High-performance, large-scale ML systems
• Language modeling with transformers
• Reinforcement learning
• Large-scale ETL

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking an ML Infrastructure Engineering Manager to lead a critical team within our Safeguards organization. You'll manage and grow a team of infrastructure engineers who build and scale the foundational systems that power our AI safety and trust mechanisms. This role combines deep technical leadership in ML infrastructure with people management, driving both the strategic vision and day-to-day execution of systems that ensure our AI models operate safely and reliably at scale. Your team will be responsible for the infrastructure backbone that enables real-time safety evaluations and systems to make Claude safe. You'll work closely with research teams to translate cutting-edge safety research into production-ready systems, while partnering with Safeguards, Security, and Alignment teams to ensure our infrastructure meets the demanding requirements of safety-critical applications. Responsibilities Set team vision and roadmap for ML infrastructure that powers Anthropic's safety and trust systems, ensuring scalability, reliability, and performance at production scale Lead a team of ML infrastructure and software engineers to build robust platforms supporting real-time safety evaluations, feature stores, model serving, and data pipelines Partner with Safeguards, Security, Research, and Product teams to identify infrastructure requirements and translate complex safety research into scalable production systems Drive technical strategy for ML infrastructure architecture, making key decisions about technology choices, system design, and platform evolution Maintain deep technical expertise in ML infrastructure, distributed systems, and safety-critical applications to provide technical leadership and guidance Hire, support, and develop team members through continuous feedback, career coaching, and people management practices Collaborate across teams to ensure infrastructure supports rapid experimentation while maintaining production reliability and safety standards Champion engineering best practices including automated testing, deployment pipelines, monitoring, and incident response for safety-critical systems You may be a good fit if you Have 4+ years of management experience leading technical teams focused on ML infrastructure, platform engineering, or distributed systems Have 8+ years of hands-on experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment Demonstrated ability to lead and manage high-performing technical teams through periods of rapid growth and scaling challenges Possess deep technical knowledge of ML serving platforms, feature stores, data pipelines, and distributed systems architecture Show excellent communication skills in translating complex technical concepts for various audiences, from individual contributors to executive leadership Have strong project management skills with the ability to balance multiple priorities and coordinate across cross-functional teams Experience managing teams that bridge research and production, with a track record of productionizing experimental systems Strong candidates may also Possess knowledge of modern ML frameworks, cloud platforms, and container orchestration in production environments Excel at building strong relationships with research teams and translating their needs into infrastructure requirements Have experience implementing automated testing, deployment, and monitoring systems for ML models in production Demonstrate passion for ensuring the responsible development and deployment of AI systems Have managed teams working on real-time, high-throughput systems with strict latency and reliability requirements Experience with compliance and security requirements for safety-critical applications At Anthropic, we value diversity and are committed to creating an inclusive environment for all employees. We encourage applications from candidates of all backgrounds. Deadline to apply: None. Applications will be reviewed on a rolling basis. The expected salary range for this position is: $405,000 - $485,000 USD Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas. However, we aren't able to successfully sponsor visas for every role and every candidate. If we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process Apply for this job To apply, submit your resume and complete the application through our careers portal. #J-18808-Ljbffr

• Detect and investigate CBRN threats: Identify and thoroughly investigate attempts to misuse Anthropic's AI systems for developing, enhancing, or disseminating CBRNE weapons, pathogens, toxins, or other CBRNE threats to harm people, critical infrastructure, or the environment. The primary focus will be on biological and chemical harms.
• Cross-platform threat analysis: Ground investigations in real threat actor behavior, basing findings off of cross-internet and open-source research, as well as past publicly reported programs.
• Conduct technical investigations: Utilize SQL, Python, and other technical tools to analyze large datasets, trace user behavior patterns, and uncover sophisticated CBRNE threat actors across our platform.
• Create actionable intelligence: Develop detailed threat intelligence reports on biological attack vectors, vulnerabilities, and threat actor TTPs leveraging AI systems, with specific focus on biodefense implications.
• Develop biological-specific detection capabilities: Create abuse signals, tracking strategies, and detection methodologies specifically tailored to identify users attempting dual-use biological misuse, including emerging biothreat vectors and novel attack patterns.
• Collaborate with policy & enforcement teams: Work closely with policy & enforcement teams to make informed decisions about user violations related to biological threats and ensure appropriate mitigation actions.
• External stakeholder engagement: Communicate findings with external partners including government agencies, regulatory bodies, scientific organizations, and biosecurity research communities.

• Have biological and chemical domain expertise: Possess deep knowledge in biosecurity, biological weapons non-proliferation, dual-use research of concern (DURC), biodefense, synthetic biology, or related biological threat domains
• Strong technical investigation skills: Demonstrated experience in technical analysis and investigations, with proficiency in SQL, Python, and data analysis tools for threat detection and user behavior analysis
• Threat intelligence or Targeting background: Experience in threat actor profiling, utilizing threat intelligence frameworks, and conducting adversarial analysis, particularly in biosecurity or related domains
• Experience with AI systems: Have hands-on experience with large language models and deep understanding of how AI technology could potentially be misused for biological threats
• Cross-functional collaboration: Excellent stakeholder management skills and ability to work effectively with diverse teams including researchers, policy experts, legal teams, and external partners
• Communication skills: Ability to present analytical work to both technical and non-technical audiences, including government stakeholders and senior leadership

• Advanced degree (MS or PhD) in biological sciences, biodefense, biosecurity, or related field, or equivalent professional experience
• Real world experience countering weapons of mass destruction, CBRNE, or other high risk dangerous asymmetric threats
• 3+ years of experience in biosecurity threat analysis, biological defense, or related investigative roles
• Comfortable with SQL and Python
• Experience working with government agencies or in regulated environments dealing with sensitive biological information
• Background in AI safety, machine learning security, or technology abuse investigation
• Familiarity with synthetic biology, biotechnology, or dual-use biological research
• Experience building and scaling threat detection systems or abuse monitoring programs