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Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. As a Temporary Clinical Research Associate, you will provide monitoring and clinical operations support across WHOOP’s portfolio of clinical research studies. You will support assigned studies at various stages of the clinical lifecycle, including startup, active study conduct, monitoring, and closeout. You will conduct monitoring activities, review study documentation, support Trial Master File quality, track study issues, and help ensure that studies are conducted in accordance with approved protocols, Good Clinical Practice, applicable regulations, and WHOOP procedures. This role requires a detail-oriented and collaborative CRA who can independently manage assigned monitoring activities, communicate effectively with research sites and internal teams, and escalate risks or compliance concerns appropriately. Depending on study timelines and business needs, you may support one or more studies during the contract period. This is a 6 month, temporary position with an hourly pay rate of $45/hr. RESPONSIBILITIES: - Conduct remote and onsite monitoring activities for assigned studies, including Site Initiation Visits, Interim Monitoring Visits, Closeout Visits, and other study-specific visits. - Perform monitoring activities in accordance with approved protocols, monitoring plans, Good Clinical Practice, applicable regulations, and WHOOP procedures. - Review informed consent documentation, participant eligibility, source documentation, case report forms, protocol adherence, safety documentation, and study data for accuracy and completeness. - Prepare accurate and timely monitoring visit reports, follow-up communications, action-item trackers, and study status updates. - Identify, document, track, and escalate protocol deviations, data quality concerns, safety issues, compliance risks, and operational challenges. - Support site readiness activities, including review of essential documents, training completion, systems access, and operational preparedness. - Assist with site and study team training on protocols, study procedures, documentation requirements, and clinical systems. - Create and maintain assigned study logs, trackers, monitoring templates, and clinical operations documentation. - Collaborate with Clinical Operations, Clinical Science, Clinical Research Coordinators, Data Management, Regulatory, Quality, investigators, research sites, and external vendors. - Support study closeout activities, including document reconciliation, action-item resolution, final monitoring activities, and Trial Master File completion. QUALIFICATIONS - Bachelor’s degree in life sciences, nursing, public health, clinical research, or a related field, or equivalent relevant experience. - 3+ years of experience in clinical research, including at least 1 year performing clinical monitoring or CRA responsibilities. - Strong attention to detail and the ability to identify and clearly document study risks, compliance concerns, and data quality issues. - Strong written communication skills, including the ability to prepare clear monitoring reports and site follow-up correspondence. DESIRED: - Experience supporting medical-device, digital-health, wearable-technology, or remote-monitoring studies. - Familiarity with ISO 14155 or clinical research involving medical devices. - Experience working in a sponsor, CRO, or research-site environment. - Experience supporting studies related to cardiovascular health, women’s health, sleep, metabolic health, or digital biomarkers.

Location: Hybrid About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. The Role: We are seeking a highly skilled AI Security Research & Red team engineer to join our Red Team within the Security Threat Detection, Response and Emulation organization. This is a critical role that will be at the forefront of protecting our company and customers from malicious threats. You will be responsible for driving security research, exercises, and activities that emulate real world attackers and attacks to drive improvements in Cloudflare’s security posture focusing on AI, Agents, harnesses and LLM’s. Key Responsibilities: AI Security and Vulnerability Research: Stay current with emerging threats and perform deep-dive research to identify AI-specific vulnerabilities and risks in addition to general vulnerabilities across Cloudflare’s products and services. Agentic testing and adoption: As a core function, identifying AI-related attack surfaces through rigorous testing of agentic implementations and LLM usage which will help  define requirements and implementation guidance while proactively. Adversary Simulation: Execution of full-chain red team operations targeting Cloudflare’s global infrastructure, corporate networks, and product ecosystems. Efficacy Testing: Establish a rigorous framework for testing "Security Efficacy"—measuring exactly how well our WAF, EDR, and SIEM detections perform against known TTPs (Tactics, Techniques, and Procedures). Purple Teaming: Foster a highly collaborative relationship with the Blue Team (Detection & Response) to ensure findings are translated into immediate defensive improvements. Mentorship & Growth: Be a technical leader, providing technical expertise while fostering a culture of curiosity, ethical hacking and partnering to improve Cloudflare’s security posture. Executive Reporting: Translate complex technical exploits into risk-based narratives for leadership, helping prioritize engineering resources where they matter most. Partnerships Security Incident Response Team (SIRT): You will act as the "sparring partner" for SIRT. By conducting unannounced exercises, you help them refine their playbooks, test their on-call rotations, and ensure their forensic tooling is effective under pressure. Threat Detection & Threat Engineering: You will partner closely with these teams to bridge the gap between adversary simulation and defensive coverage. You will proactively identify detection gaps, lead the development of new detection logic, and establish rigorous validation frameworks to test and tune detections against emerging TTPs. Product Engineering/SRE: We operate as "Customer Zero" of our own products, your red teaming findings will drive resilience in processes and implementations, ultimately making Cloudflare and its customers more secure. Governance, Risk, and Compliance (GRC): You will bridge the gap between "paper security" and "technical reality." By providing empirical evidence of control effectiveness, you help GRC move away from manual audits and toward continuous, automated compliance validation. Required Qualifications: Experience: 4+ years in offensive security, application security or other relevant field Deep knowledge: AI, Coding agents, LLMs, prompt engineering, AI-related attack vectors (e.g., prompt injection, jailbreaking), and Agentic concepts all for use in the red team but also testing Cloudflare  uses. Technical Roots: A strong background in manual penetration testing, exploit development, or cloud security (AWS/GCP/Bare Metal). Operational Mindset: Experience using the MITRE ATT&CK framework to map coverage and identify "blind spots" in defensive telemetry. Communication Skills: The ability to explain a complex "0-day" exploit to a non-technical stakeholder while maintaining the respect of a deep-dive engineering team. Tooling Familiarity: Knowledge of automated breach and attack simulation (BAS) tools, as well as custom-built frameworks for payload delivery and C2 infrastructure. Compensation Compensation may be adjusted depending on work location. For New York based hires: Estimated annual salary of $166,000 - $208,000. Equity This role is eligible to participate in Cloudflare’s equity plan. What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

Location: United States Workplace: remote About Lyra Health Lyra Health is a leading provider of evidence-based mental health care, serving more than 20 million people globally in partnership with employers and more than 100 million through health plan and partner relationships. The company has delivered more than 15 million sessions of mental health care, published more than 35 peer-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness, and cost efficiency. Extensive peer-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life-changing mental health care through Lyra Empower, the only fully integrated, AI-powered platform combining the highest-quality care and technology solutions. About the Role:  Lyra is transforming mental health care by creating a frictionless experience for members, providers, and employers. We connect companies and their employees to mental health providers, therapy, and coaching programs that work. We are looking for a self-driven, technical Data Scientist who cares about impact, ownership and innovation. In this role, you will work closely with Lyra’s Data, Product, Engineering, and Clinical teams on AI/ML initiatives that will enhance the experience of mental health patients and providers.  This Data Scientist role can be filled remotely anywhere within the US, as well as locally in our Burlingame, CA headquarters.  Please note that remote-based candidates must be physically located within the United States. Responsibilities Work closely with Lyra’s Data, Product, Engineering, and other associated teams to enhance the Lyra platform to serve the needs of our providers and clients. Become an expert in the diverse data sources we collect and partner with data engineers to build pipelines that apply clinical logic to raw data Extract actionable insights, develop predictive and generative models, and implement rigorous evaluation frameworks to support product iterations Complete time-sensitive ad hoc data requests for internal and external stakeholders Qualifications 5+ years of data analysis in an industry setting with a preference for individuals who have experience in product analytics in the AI/ML space and have partnered with engineering and product teams in prior roles. Experience collaborating with cross-functional stakeholders across technical, business, and (ideally) clinical domains Demonstrated understanding of statistical applications and methods (experimentation, probabilities, regression).  Experience applying hypothesis testing in an industry or research setting. Experience developing comprehensive analyses using irregular data from disparate sources.  Willing to do whatever it takes to clean messy data prior to deriving insights. Strong SQL proficiency.  Experience writing complex queries with multiple schemas and tables.  Preference for candidates who have experience creating views. Graduate-level Statistics coursework with MS in a quantitative field is preferred (statistics, econometrics, biostatistics, quantitative social sciences). Preferred Qualifications Interest in public health a plus Experience with AI/ML R&D, e.g. prompt engineering and RAG Experience with Python, including cleaning and analyzing data as well as using Python to parse JSON structured data, call APIs, create user-defined functions, and automate. "We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law.   By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra.  We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR.  Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives.  If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form.  This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact globaldpo@lyrahealth.com. For more information about how we use and retain your information, please see our Workforce Privacy Notice." As a full-time Sr. Data Scientist - AI Research, you will be employed by Lyra Health, Inc. The anticipated annual base salary range for this full-time position is $128,000 to $197,000. The base range is determined by role and level, and placement within the range will depend on a number of job-related factors, including but not limited to your skills, qualifications, experience and location. This role may also be eligible for discretionary bonuses.  Annual salary is only one part of an employee’s total compensation package at Lyra. We also offer generous benefits that include:  Comprehensive healthcare coverage (including medical, dental, vision, FSA/HSA, life and disability insurances) Lyra for Lyrians; coaching and therapy services Equity in the company through discretionary restricted stock units Competitive time off with pay policies including vacation, sick days, and company holidays Paid parental leave  401K with up to 3% matching Monthly tech allowance We like to spread joy throughout the year with well-being perks and activities, surprise swag, regular community celebration…and more!   We can’t wait to meet you.

Location: USA Workplace: Remote We are looking for doctors and medical experts to join our growing community of experts who are available to be matched on an on-going basis to new innovative AI projects with the world's leading AI labs and companies that are bringing to life AI in healthcare.   Your medical expertise will shape the way AI understands and processes real-world clinical interactions, workflows, consultations including the delivery of care with software that directly impacts both healthcare professionals and patients.   These projects are flexible, fully remote and ideal for clinicians who want to work on shaping the future of AI in healthcare alongside their existing professional or academic commitments.   ABOUT MENTIS AI   At Mentis AI, we’re building the next generation of AI systems grounded in real-world clinical expertise. As a clinical expert, you’ll gain hands-on exposure to cutting-edge AI model development, working side-by-side with senior AI researchers and clinicians to translate your medical knowledge into industry-ready clinical solutions to advance healthcare.   HOW IT WORKS   Once we have a new project, you will be automatically screened and matched to assess if you are a suitable fit. If shortlisted, we will then invite you to take a skills test (~10-30mins) and if required will also conduct an interview.   We are looking to match you based on your skillset, expertise, grade and speciality to make sure it's the right fit for the project!   If successful, you will be onboarded onto the platform and can start getting involved in a diverse range of tasks that vary from labelling clinical notes, summarising medical records, annotating images to reviewing and evaluating the performance of AI Models/LLMs.   The rapid rise of AI in healthcare means there are so many new and exciting ways to train, review and improve the deployment of AI in healthcare, which you will directly have an impact upon.   KEY RESPONSIBILITIES   - Data labeling and curation: Review clinical notes, audio, videos and other modalities, identifying relations and reasoning steps per guidelines. - LLM and model evaluations: Run structured evals (human-in-the-loop) to assess accuracy, safety, clinical relevance and clinical reasoning of models. - Prompting and prompt-engineering: Design, test, and iterate prompts to improve performance and reliability. - Fine-tuning support: Create high-quality instructions/responses and explore edge-case datasets to enhance models. - Feedback and error analysis: Identify critical/failure points, propose strategies to help mediate and document findings. - Scoring/Rubrics frameworks: Develop and refine scoring rubrics for quality assurance (e.g., accuracy, clarity, safety, completeness, guideline adherence). - Guideline refinement: Collaborate with researchers to improve annotation standards, acceptance criteria, and evaluation protocols.   ESSENTIAL REQUIREMENTS   - Doctor based in the US with active license to practice. - Native or near-native fluency in English (spoken and written). - Good understanding of clinical terminology, tools and workflows. - Excellent summarisation and written communication skills. - Strong attention to detail and commitment to clinical accuracy. - Comfortable working independently in an asynchronous environment.   WHAT WE OFFER   - Remote work - Asynchronous and flexible scheduling, allowing you to balance work with clinical practice or studies. - Competitive compensation based on experience. - The opportunity to influence and enhance AI tools that serve healthcare professionals. - Experience working at the intersection of medicine and AI, helping shape the future of healthcare. - Opportunity to collaborate with clinicians and AI researchers to deepen your own clinical acumen and professional expertise in AI within healthcare.

Location: London; United Kingdom Workplace: Remote We are looking for doctors to join our growing community of experts who are available to be matched on an on-going basis to new innovative AI projects with the world's leading AI labs and companies that are bringing to life AI in healthcare. Your medical expertise will shape the way AI understands and processes real-world clinical interactions, workflows, consultations including the delivery of care with software that directly impacts both healthcare professionals and patients. These projects are flexible, fully remote and ideal for clinicians who want to work on shaping the future of AI in healthcare alongside their existing professional or academic commitments. ABOUT MENTIS AI At Mentis AI, we’re building the next generation of AI systems grounded in real-world clinical expertise. As a clinical expert, you’ll gain hands-on exposure to cutting-edge AI model development, working side-by-side with senior AI researchers and clinicians to translate your medical knowledge into industry-ready clinical solutions to advance healthcare. HOW IT WORKS Once we have a new project, you will be automatically screened and matched to assess if you are a suitable fit. If shortlisted, we will then invite you to take a skills test (~10-30mins) and if required will also conduct an interview. We are looking to match you based on your skillset, expertise, grade and speciality to make sure it's the right fit for the project! If successful, you will be onboarded onto the platform and can start getting involved in a diverse range of tasks that vary from labelling clinical notes, summarising medical records, annotating images to reviewing and evaluating the performance of AI Models/LLMs. The rapid rise of AI in healthcare means there are so many new and exciting ways to train, review and improve the deployment of AI in healthcare, which you will directly have an impact upon. KEY RESPONSIBILITIES - Data labeling and curation: Review clinical notes, audio, videos and other modalities, identifying relations and reasoning steps per guidelines. - LLM and model evaluations: Run structured evals (human-in-the-loop) to assess accuracy, safety, clinical relevance and clinical reasoning of models. - Prompting and prompt-engineering: Design, test, and iterate prompts to improve performance and reliability. - Fine-tuning support: Create high-quality instructions/responses and explore edge-case datasets to enhance models. - Feedback and error analysis: Identify critical/failure points, propose strategies to help mediate and document findings. - Scoring/Rubrics frameworks: Develop and refine scoring rubrics for quality assurance (e.g., accuracy, clarity, safety, completeness, guideline adherence). - Guideline refinement: Collaborate with researchers to improve annotation standards, acceptance criteria, and evaluation protocols. ESSENTIAL REQUIREMENTS - Doctor based in the UK with an active GMC license. - Native or near-native fluency in English (spoken and written). - Good understanding of clinical terminology, tools and workflows. - Excellent summarisation and written communication skills. - Strong attention to detail and commitment to clinical accuracy. - Comfortable working independently in an asynchronous environment. WHAT WE OFFER - Remote work - Asynchronous and flexible scheduling, allowing you to balance work with clinical practice or studies. - Competitive compensation based on experience. - The opportunity to influence and enhance AI tools that serve healthcare professionals. - Experience working at the intersection of medicine and AI, helping shape the future of healthcare. - Opportunity to collaborate with clinicians and AI researchers to deepen your own clinical acumen and professional expertise in AI within healthcare.

Location: Hong Kong Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT : You will contribute to the efficiency of the technical environment of research. You will build and operate internal tools and services used by researchers across the firm. You will work directly with researchers to understand their workflows, identify recurring pain points, and turn them into better tooling, automation, documentation, or platform improvements. Build backend services, APIs, automation scripts, dashboards, and lightweight web applications Deploy and operate internal applications using cloud, containers, and CI/CD Improve onboarding, documentation, self-service workflows, and internal knowledge sharing Troubleshoot issues across applications, infrastructure, user environments, and integrations Work with engineering teams to improve adoption, usability, ownership, and supportability of internal platforms Contribute to secure, maintainable, observable, and scalable internal systems Your current skillset : Strong software engineering skills, preferably in Python Experience building internal tools, APIs, automation, or web applications Experience with AI-assisted and agentic software development tools Familiarity with cloud environments, containers, deployment workflows, and CI/CD Ability to debug technical issues across several layers of a system Clear written and verbal communication skills Ability to work with technical and non-technical stakeholders Pragmatic approach to problem solving, with a focus on useful outcomes Strong user-centric mindset, with the ability to understand user workflows, constraints, and pain points in depth Curiosity and willingness to learn unfamiliar tools, systems, and domains Strong interpersonal skills, with the ability to build trust, credibility, and strong working relationships with researchers QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: Amsterdam, Netherlands; London, United Kingdom; Remote - Europe; Zurich, Switzerland About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. We are seeking a Staff Applied AI Researcher to join a fast-growing team building an agent-native search platform - the web access layer for AI systems. You can think of this as Google search, but for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing these systems to search and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval, ranking and passage extraction under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24/7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. In the first year, you will own a specific part of the search stack, e.g. ranking or iterative retrieval. What you'll work on: Designing an agent-native search system that handles everything from low-latency single-hop search to complex deep search tasks requiring iterative planning, querying, refinement and reasoning. Training ranking and retrieval models optimized for agent-driven workflows under real world constraints Bringing the latest advances from the research community to our search stack and ship it to production. Your responsibilities: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi-stage retrieval architectures (query understanding, rewriting, retrieval, reranking and iterative retrieval) Lead experimentation on modern retrieval approaches (embedding research, sparse and hybrid retrieval, reranking, context compression) and bring them into production Develop methods for grounding LLMs in real-time web data at scale, using trust, quality and freshness signals to surface reliable sources Partner with the evaluation team to define new metrics for agentic systems, where correctness is not reducible to clicks Analyze trade-offs across relevance, latency, and cost, and work closely with engineering to deploy systems that operate at web scale Mentor researchers and engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking or building RAG-based assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM-integrated or knowledge-intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python Top-tier publications ( ICLR , ICML , NeurIPS, AAAI , EMNLP , ACL ) Ability to operate in a fast-moving, product-driven environment with high ownership and autonomy Nice to haves Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RL post-training of LLMs or VLMs Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: United States, Remote Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Reporting to the Director of Global Vulnerability Management, you will serve as a Senior Security Research Engineer and technical lead within SIE’s Global Vulnerability Management team. You will lead complex work that advances our Threat Exposure Management capability and supports our transition to a Continuous Threat Exposure Management operating model, while remaining directly engaged in vulnerability research, analysis, security validation, prioritization, and remediation support. You will partner across Information Security, engineering, technology, and business teams to improve how SIE discovers, prioritizes, validates, and mobilizes action on security risks. You will translate annual TEM goals into defined workstreams, delivery plans, success measures, and repeatable operating practices that improve visibility, decision-making, remediation outcomes, and program scale. Responsibilities Lead complex Global Vulnerability Management workstreams that advance SIE’s Threat Exposure Management capability and transition toward a Continuous Threat Exposure Management operating model across discovery, prioritization, validation, and mobilization. Translate annual TEM goals into defined delivery plans, milestones, success measures, dependencies, and repeatable operating practices. Monitor progress, identify barriers, and adjust execution to improve outcomes. Lead hands-on vulnerability research and technical analysis to confirm security conditions, eliminate false positives, characterize exploitability and business impact, and provide actionable remediation or mitigation guidance. Improve the discovery and assessment of vulnerabilities across SIE network, cloud, endpoint, application, container, and other technology environments. Develop risk-based prioritization using vulnerability and threat intelligence, exploitation evidence, asset and business context, control effectiveness, and remediation considerations. Lead security validation activities and develop proofs of concept when appropriate to distinguish material risk, evaluate defensive controls, and support informed decisions. Partner with Information Security teams and technology owners to mobilize remediation, clarify ownership, establish effective handoffs, resolve barriers, and measure progress through remediation, mitigation, or accepted disposition. Evolve GVM platforms, integrations, data, analytics, automation, and AI-enabled workflows to improve coverage, data quality, consistency, decision speed, and operational scale. Communicate vulnerability trends, material risks, remediation progress, and program outcomes to technical, operational, and leadership audiences through clear reports and recommendations. Mentor engineers and partner teams, contribute to technical standards and procedures, and improve the quality of vulnerability analysis, validation, documentation, and delivery. Maintain current knowledge of relevant vulnerabilities, exploitation techniques, threat activity, security technologies, and industry practices. Some travel may be required. Qualifications 8+ years of relevant experience in information security, information technology, systems engineering, or a related field, including substantial experience in vulnerability management, security research, or exposure management. Bachelor’s degree or equivalent in computer science, information security, or a related discipline. Experience leading complex technical workstreams across multiple teams, translating objectives into delivery plans, and achieving measurable outcomes without relying on direct reporting authority. Hands-on experience with vulnerability research, technical analysis, security validation, risk-based prioritization, and remediation or mitigation guidance. Experience assessing vulnerabilities across several technology domains, such as operating systems, networks, cloud services, applications, endpoints, containers, databases, or hybrid infrastructure. Experience with vulnerability discovery, assessment, validation, or exposure-management platforms and their supporting integrations. Knowledge of adversarial tactics, exploitation techniques, threat intelligence, and attack frameworks such as MITRE ATT&CK, with the ability to apply that information to vulnerability prioritization. Experience using scripting, programming, APIs, or automation to improve security analysis and operational workflows. Relevant technologies may include Python, SQL, Bash, PowerShell, JavaScript, or comparable languages. Experience analyzing and contextualizing security data to connect technical findings with asset, service, business, threat, control, and remediation information. Familiarity with software engineering practices such as version control, testing, code review, CI/CD, reusable components, and controlled production releases. Ability to communicate complex security conditions, priorities, tradeoffs, and recommendations clearly to technical, operational, and leadership audiences. Experience mentoring engineers or analysts and influencing technical practices across teams. Desired qualifications Experience helping evolve a traditional vulnerability-management function toward a TEM or CTEM operating model. Experience with continuous security validation, adversarial exposure validation, exploit research, or proof-of-concept development. Experience securing cloud, container, application, or build-pipeline environments and integrating security capabilities into engineering workflows. Experience with security-data and analytics platforms such as Snowflake, Domo, or comparable technologies. Experience applying automation, advanced analytics, or AI-enabled capabilities to vulnerability analysis, prioritization, validation, or remediation workflows. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. This is a flexible role that can be remote, with varying pay ranges based on geographic location. For example, if you are based out of Seattle, the estimated base pay range for this role is listed below. $175,500 — $263,300 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: San Francisco, CA | New York City, NY 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 Team Our Reinforcement Learning teams are central to advancing our AI systems, contributing to every Claude model and driving the autonomy and coding gains in our latest releases. The work spans computer use, code generation through RL, fundamental RL research for large language models, scalable infrastructure and training methodologies, and model reasoning. Research TPM team supports the full model development lifecycle, from pre-training through post-training, operating at the frontier of AI development. About the Role As a Technical Program Manager on the reinforcement learning team, you will own the systems and programs that determine how fast our research moves: a trustworthy read on the state of RL research, the review and prioritization processes that turn that read into critical decision for production RL runs. Strong candidates should have an ML engineering or research background and have grown into program leadership. You'll need real technical depth: the ability to debug data pipelines, read RL transcripts to spot issues, and make allocation and quality decisions in real time when research or production runs hit problems. You'll need organizational effectiveness in equal measure: the ability to navigate a fast-growing organization, quickly identify the critical people and teams across research, infrastructure, product, and data operations, and coordinate across them without losing velocity. Join us in our mission to build AI systems that are safe, reliable, and beneficial to humanity. Responsibilities Deliver a regular read on the ground truth in RL research, covering performance against baselines, experiment results, day-to-day health, and incidents Work with RL org leads on prioritizing, ranking, and tracking the state of experiments Drive research reviews end to end in partnership with set the agenda, make sure the right context is in the room ahead of time, and close the loop on what gets decided Establish processes and frameworks that bring structure to an unstructured research setting without slowing researchers down Collaborate with research leads, infrastructure engineers, and data operations to identify blockers, prioritize competing needs, and make technical trade-off decisions You May Be a Good Fit If You Have a background in ML engineering or ML research before transitioning to technical program management Have deep, hands-on experience with ML training pipelines, RLHF systems, and large-scale data infrastructure in production Have a track record of building execution plans and inventing high-leverage processes that reduce operational overhead and let researchers focus on research Are a fast learner who builds deep contextual understanding in unfamiliar technical domains and can contribute meaningfully to discussions with researchers Are resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in a fast-moving research setting Have excellent stakeholder management and communication skills, with the ability to influence senior technical staff through clarity, competence, and consistent delivery Are excited about pushing the frontier of what RL can do at scale The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $365,000 — $435,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. But 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. 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.

Location: Palo Alto Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE This role focuses on building and operating the end-to-end execution, training, and data infrastructure that powers Mistral’s agentic models and coding assistants. You will be a core contributor to our agent research stack: designing scalable systems for synthetic data generation, building ultra-fast training and RL execution environments, and maintaining high-throughput execution engines. You will tackle the engineering challenges at every step of the agent lifecycle: from orchestrating 1M+ concurrent and short-lived sandboxes for untrusted code execution to optimizing agent training codebases, distributed trajectory collection pipelines, and dataset processing workflows across massive hybrid and multi-cloud clusters. WHAT YOU WILL DO - Large-Scale Sandboxing Infrastructure: Design, deploy, and operate our high-throughput sandboxing platform, executing LLM-generated untrusted code across over 1 million isolated environments concurrently for model evaluation and interactive RL environments. - Agent Data Generation Pipelines: Architect and scale high-throughput pipelines for synthetic code generation, agent trajectories, rollouts, and self-play data collection to power post-training and RL loops. - Training Codebase & Systems Optimization: Optimize agent training codebases and distributed execution runtimes (PyTorch, Ray, SLURM/Kubernetes) to minimize multi-step rollout overhead, improve GPU utilization, and eliminate scaling bottlenecks. - Low-Latency Orchestration & Warm Pooling: Reduce sandbox cold-start times to sub-second levels using container warm pools, snapshot/restore technology (e.g., CRIU, microVMs), and optimized image delivery layers across hybrid clusters. - Multi-Cluster Queueing & Resource Allocation: Implement Kubernetes-native custom controllers, CRDs, and queuing systems to dynamically route short-lived evaluation, synthetic data, and agent execution tasks across diverse hardware fleets. - Isolation, Security & Security Boundary: Ensure strict multi-tenant network and process isolation for untrusted agent code using container/sandboxing runtimes (e.g., gVisor, Firecracker) and default-deny network postures. - Operational Excellence: Maintain high availability, telemetry, and automated self-healing across millions of transient jobs while participating in on-call rotations for critical agent training and execution pipelines. WHAT WE'RE LOOKING FOR - 4+ years of experience in Systems Engineering, Distributed Systems, Cloud Infrastructure, or MLOps supporting LLM/RL workloads. - Data & Pipeline Engineering: Proven experience building high-throughput data processing and generation pipelines for large-scale datasets (e.g., Ray, Spark, custom distributed queues). - Deep experience with Kubernetes & Container Tech: Strong expertise writing custom K8s operators/controllers, managing Linux cgroups/namespaces, and optimizing Docker image layers and distribution systems. - High-Performance Software Engineering: Advanced proficiency in Python, Go, C++ or Rust, with a track record of profiling and optimizing high-performance ML or backend systems codebases. - Sandboxing & Isolation Technologies: Hands-on experience with lightweight virtualization, container runtimes, or WASM (e.g., Docker, gVisor, Firecracker). - Queueing & Scheduling: Deep familiarity with task queue systems, resource schedulers, and low-latency queuing architectures for high-volume, short-lived workloads. - Comfort with Ambiguity: Passion for working directly alongside AI researchers to rapidly turn frontier agent ideas into scalable, production-grade infrastructure. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Paris Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology- and data-driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors. Your future role within QRT: You will contribute to the engineering platform that supports quantitative research across the firm. Working closely with researchers and software engineers, you will build and improve internal tools and services that simplify workflows, automate repetitive tasks, and enhance the overall research experience. Build and maintain backend services, APIs, automation tools, dashboards, and lightweight web applications Develop internal tooling and self-service solutions that improve researcher productivity Deploy and operate internal applications using cloud technologies, containers, and CI/CD Work directly with researchers to understand their workflows and turn recurring pain points into practical engineering solutions Troubleshoot issues across applications, infrastructure, development environments, and integrations Improve documentation, onboarding, and internal knowledge sharing Collaborate with engineering teams to improve the usability, reliability, and adoption of internal platforms Your present skillset: Strong software engineering skills, preferably in Python Experience building internal tools, APIs, automation, or web applications Experience using AI-assisted and agentic software development tools Familiarity with cloud environments, containers, deployment workflows, and CI/CD Ability to troubleshoot technical issues across applications and infrastructure Clear written and verbal communication skills Ability to collaborate effectively with technical and non-technical stakeholders Pragmatic problem-solving skills with a strong user-focused mindset Curiosity and willingness to learn new tools, technologies, and domains Strong interpersonal skills and the ability to build trusted relationships with researchers QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: New York; San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. WHAT YOU’LL WORK ON: - Improve existing methods and develop new techniques for large-scale model training, optimization, and inference - Extend models to long-context and long-horizon tasks - Improve inference-time efficiency, reliability, and robustness in high-stakes real-world deployments YOU MAY BE A FIT IF: - You’re currently pursuing a PhD in computer science, machine learning, or a related field - You have a demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas - You have experience developing and evaluating large-scale models or machine learning systems - You’re familiar with distributed training, large-scale inference, or multi-GPU environments - You have publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR - You have strong programming and engineering skills and can translate research ideas into working implementations - You have a collaborative, mission-driven mindset and can work effectively across research and engineering teams

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a VP of Research (Machine Learning) to define and lead the research direction behind its AI platform. This leadership role will shape how AI systems reason, learn, evaluate, and continuously improve within a product designed for high-frequency, real-world usage. Working closely with product and engineering leadership, this position will drive the long-term intelligence strategy, balancing cutting-edge research with practical production impact. Key Responsibilities Define and evolve the research roadmap for the platform's core AI intelligence, including context representation, memory, reasoning, planning, and orchestration. Evaluate and determine when to develop proprietary model architectures versus leveraging or adapting frontier open-source and commercial AI models. Design evaluation frameworks that measure real-world performance, robustness, safety, and long-term system behavior beyond traditional benchmark metrics. Lead the company's AI alignment, safety, and guardrail strategy as a core component of product development. Drive research and experimentation across advanced machine learning techniques, including: Retrieval-Augmented Training (RAG) Mixture of Experts (MoE) Model Distillation Multi-Agent Orchestration Multimodal AI Systems Partner closely with product and engineering teams to define and execute the intelligence strategy for AI-powered applications. Establish and maintain high standards for research quality, technical judgment, and engineering excellence across the organization. Requirements Extensive experience designing, building, and deploying machine learning systems in production environments. Strong technical expertise in model behavior, failure analysis, system evaluation, and long-term AI performance. Proven ability to translate advanced research into reliable, production-ready AI solutions. Demonstrated experience making high-impact technical decisions in fast-moving and ambiguous environments. Deep understanding of AI evaluation methodologies, model robustness, safety, and system reliability. Strong ownership mindset with the ability to lead technical strategy and execution. Passion for building practical AI systems that deliver measurable real-world impact rather than focusing solely on academic research or benchmark performance. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based model training and inference systems

Location: Santa Clara, CA Step into the innovative world of LG Electronics. As a global leader in technology, LG Electronics is dedicated to creating innovative solutions for a better life. Our brand promise, 'Life's Good', embodies our commitment to ensuring a happier life for all. We have a rich history spanning over six decades and a global presence in over 290 locations.  Our diverse portfolio includes Home Appliance Solutions, Media Entertainment Solutions, Vehicle Solutions, and Eco Solutions.  Our management philosophy, "Jeong-do Management," embodies our commitment to high ethical standards and transparent operations. Grounded in the principles of 'Customer-Value Creation' and 'People-Oriented Management', these values shape our corporate culture, fostering creativity, diversity, and integrity. At LG, we believe in the power of collective wisdom through an inclusive work environment.  Join us and become a part of a company that is shaping the future of technology.  At LG, we strive to make Life Good for Everyone. About the Team - LG's Emerging Technology Lab LG's Emerging Technology Lab (ETL) is the catalyst for technological innovation within LG’s CTO organization. Located in the Silicon Valley and New Jersey, we drive excellence across CTO organizations and business units by pioneering in select emerging technology areas. As the Center of Excellence (CoE), we define and shape key technology domains, setting strategic directions that foster impactful internal and external partnerships to deliver measurable business value. About the Opportunity We are seeking a Contract AI Researcher - Efficient AI to join LG's Emerging Technology Lab in Santa Clara, CA (hybrid). This is an exciting opportunity to work at the forefront of AI efficiency research, developing technologies that make modern LLMs, VLMs, multimodal models, and AI agents faster, smaller, and more deployable in real-world environments. In this role, you will explore cutting-edge areas such as model compression, quantization, efficient inference, reasoning optimization, and next-generation AI architectures. Your work will help enable advanced AI capabilities across LG's future products and platforms, including AI PCs, edge devices, robotics, and intelligent vehicle systems. The ideal candidate enjoys bridging research and implementation, transforming ideas from the latest scientific literature into working prototypes and measurable improvements. You will have the opportunity to collaborate with experienced researchers, contribute to publications and intellectual property, and help shape the future of efficient, on-device AI. Responsibilities •    Research, prototype, and implement AI methods that improve model efficiency, inference performance, and deployment feasibility on constrained devices. •    Optimize modern LLMs, SLMs, VLMs, multimodal models, and agentic workloads across post-training, inference, and deployment workflows. •    Propose and evaluate novel compression methods (PTQ, QAT, pruning, low-rank approximation, etc) for on-device LLM/VLM enablement. •    Devise approaches to address challenges related to long-context inference and KV cache compression in the context of reasoning and agentic applications. •    Develop gradient-free and backpropagation-free methods for model merging, compression, and efficiency-driven optimization. •    Implement and evaluate emerging efficient architectures and modules, including MoE, SSMs, hybrid models, Looped Transformers, etc. •    Prototype inference-time optimization methods such as speculative decoding, constrained decoding, low-latency generation, and kernel-level optimization. •    Build experimental pipelines, perform evaluations on standardized language, vision, reasoning, and agentic benchmarks. •    Contribute to publications, technical reports, open-source releases, invention disclosures, and IP submissions where appropriate. Required Qualifications •    M.S. or Ph.D. in Computer Science, Computer Engineering, Machine Learning, Mathematics, or a related technical field. Relevant post-graduate research and/or industry experience is preferred but not required. •    Research or engineering experience in ML, efficient AI, model optimization, or AI systems. •    Strong programming ability in Python and experience with PyTorch or a comparable deep learning framework. •    Hands-on experience with modern LLMs, SLMs, VLMs, multimodal models, or generative AI systems. •    Ability to read research papers, implement technical methods, run experiments, and communicate results clearly. •    Comfortable working in a fast-moving and ambiguous technical environment. •    Strong written and verbal communication skills for reports, presentations, demos, and technical documentation. Ways to Stand Out •    Publications in reputable venues in ML and/or systems space (e.g., ICML, ICLR, NeurIPS, ACL, COLM, EMNLP, MLSys, MICRO, etc). •    Experience with modern LLM/VLM inference and deployment frameworks such as llama.cpp, GGUF, vLLM, SGLang, TensorRT-LLM, or related systems. •    Experience with efficiency-aware post-training or finetuning methods such as PTQ, QAT, LoRA, distillation, instruction tuning, DPO, OPD, RLVR, or reasoning-oriented adaptation. •    Experience with low-level kernel implementations and on-device acceleration. •    Familiarity with emerging architectures such as MoE, SSMs, hybrid attention, or Looped Transformers. •    Experience with AI-assisted optimization, multi-agent systems, or agentic-based workflows for Efficient AI and hardware/software co-design. Contract: This is expected to be a one-year contract position, with the potential for extension based on business needs and performance. Third-Party Agency Notice: We are not accepting unsolicited resumes or candidate submission from staffing agencies or search firms for this position. Please do not contact us regarding this opportunity. #LI-JH1 #Hybrid Recruiting Range $84.13 — $91.34 USD Benefits Offered Full-Time Employees: No-cost employee premiums for you and your eligible dependents for competitive medical, dental, vision and prescription benefits. Auto enrollment with immediate vesting of competitive company matching contributions in a 401(k) Retirement Savings Plan with several investment options. Generous Paid Time Off program that includes company holidays and a combined bank of paid sick and vacation time. Performance based Short-Term Incentives (varies by role). Access to confidential mental health resources to help you and your loved ones improve your quality of life. Personal fitness goal incentives. Family orientated benefits such as paid parental leave and support for families raising children with learning, social, behavioral challenges, or developmental disabilities. Group Rate Life and Disability Insurance. Benefits Offered Temporary/Contractors: Eligible for the relevant benefit programs offered through our partner agencies. Privacy Notice to California Applicants Applicants who need assistance or a reasonable accommodation during the hiring process may contact our team by phone at: 973-477-7090 or support@lg4me.freshdesk.com. This email and phone number will only reply to accommodation requests and is not intended for general employment inquiries. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. In addition to the above, LG believes that pay transparency is a key part of diversity, equity, and inclusion. Our salary ranges take into account many factors in making compensation decisions including but not limited to skillset, experience, licensure, certifications, internal equity, and other business needs. While we consider geographic pay differentials in final offers, because we operate in many geographies where applicable, the salary range listed may not reflect all geographic differentials applied .

Location: San Francisco, CA | New York City, NY 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's Safeguards team builds the systems that detect and mitigate misuse of our AI models, from individual policy violations to sophisticated, coordinated attacks. A growing part of that work depends on lightweight detection methods trained on model internals, which let us identify harmful behavior cheaply and at scale. This work feeds directly into Anthropic's Responsible Scaling Policy commitments. We're looking for an engineer to own the infrastructure behind that research. This is the tooling our researchers rely on to run experiments, train detection methods, and select detections for launch. It sits between research and production: researchers depend on it for fast iteration, and our detection systems depend on it for reliable, correct results as our models continue to change. Running machine learning workloads at our scale often requires solving novel systems problems. You'll identify those problems and build the abstractions, pipelines, and tooling that keep the research loop fast as requirements shift underneath you. Strong candidates will have a track record of solving large-scale systems and data problems and will be excited to grow deep machine learning expertise alongside it. Key responsibilities Build and scale the infrastructure and data pipelines behind Safeguards machine learning research Own the training, evaluation, and scoring workflows researchers use, with a focus on cutting the time between an idea and a result Design tooling and interfaces, including libraries and command line tools, that researchers can use directly without needing to understand the systems underneath Build correctness and sanity checking into the stack, so results stay trustworthy as models and workloads evolve Take the highest-value research workflows from experiments to reliable, production-grade jobs Improve the throughput, cost, and reliability of large-scale inference and scoring workloads Partner closely with researchers and engineers across Safeguards to understand their workflows, anticipate how their needs will change, and design for that ahead of time Minimum qualifications Strong software engineering fundamentals and hands-on coding ability, with proficiency in Python Experience building and operating data-intensive or distributed systems in production Experience building tooling or infrastructure that other engineers or researchers use as a dependency Comfort working across the research-to-deployment pipeline, from exploratory experiments to production systems Ability to debug performance and correctness problems across an unfamiliar stack Strong written and verbal communication skills, and a collaborative approach to technical decisions Preferred qualifications Experience with high-performance, large-scale machine learning systems Familiarity with language modeling and transformers, including working with model internals Experience with machine learning framework internals, GPU or accelerator programming, or inference optimization Experience building experiment tracking, caching layers, or evaluation harnesses for research teams Experience with probes, interpretability, or classifier development Interest in the misuse risks of AI systems and a desire to work on mitigating them The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. But 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. 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.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. By providing members with a deep understanding of their bodies, behaviors, and daily lives, WHOOP empowers healthier choices and peak performance. We are seeking a Principal AI Researcher to join our Foundation AI team. This team builds the foundation models that underpin WHOOP’s next generation of intelligent, personalized, and health-enhancing experiences. These models integrate data across wearable sensors, language, biomarkers, clinical information, and self-reported inputs to create scalable AI systems that understand human physiology and behavior. In this role, you'll be one of the senior technical leaders at WHOOP.  You will own the technical execution of our foundation modeling workstreams and your technical judgment will shape a core part of WHOOP’s AI efforts and the products they power. RESPONSIBILITIES: - Set the architectural direction for the development of large-scale models spanning wearable sensor data, text, biomarkers, and behavioral signals, and personally own the highest-stakes, hardest-to-reverse design decisions. - Identify which research bets in self-supervised and representation learning are worth making, and drive the most ambiguous and unproven ones from thesis to validated, production capability. - Contribute to the broader AI  strategy and standards at WHOOP, shaping the platform, compute, and infrastructure choices the team operates on, not just working within them. - Partner across research, product, and engineering to connect technical breakthroughs to product and business outcomes. - Raise the technical bar across the team: grow staff and senior engineers, strengthen design-review and evaluation norms, and act as a force multiplier. - Represent WHOOP's technical work externally, helping with recruiting, partnerships, and visibility in the broader AI research community. QUALIFICATIONS: - Advanced degree (Master’s or Ph.D.) or equivalent depth, with extensive experience in large-scale machine learning and AI research. - A track record of owning technical direction for a significant area and making architectural decisions whose impact outlived any single project. - Demonstrated ability to take ambiguous, high-risk research directions all the way to production impact and the judgment to discontinue those that will not. - Deep expertise in modern deep learning (transformers, state space models), multimodal training, self-supervised and representation learning, RL-based post-training (PPO/DPO/GRPO), and large-scale distributed training (data, model, and context parallelism). - A history of being a technical authority that teams defer to, and evidence of multiplying their output. - Excellent communication and the ability to influence both the engineering bench and senior leadership. - Publications and evidence of community building at top-tier machine learning venues.  - Passion for WHOOP's mission to improve human performance and extend healthspan through science and technology.  This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.  Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility.  It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $270,000 - $300,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.  In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Location: United States of America What We Do: Cybercrime is growing, and more businesses are getting hit by threats that used to target only the biggest organizations. That pushes defenders like us to operate at the highest level, and it deepens our need for good people who want to make a meaningful impact. Founded in 2015 by former NSA cyber operators, Huntress is a remote-first team working to make enterprise-grade cybersecurity accessible to businesses of all sizes. We work closely with security teams and service providers protecting complex environments, often without the time or headcount to handle it all. That’s why we build our technology in-house and back it with a 24/7 human-led Security Operations Center (SOC). As a result, our platform is never disconnected from the experts who manage it, ensuring our customers' protection. Huntress now secures more than 6M endpoints and 17M identities worldwide. Those numbers keep growing because more businesses rely on us to help carry the load and operate with more confidence. Every day, you can see that commitment in how we stand with our customers and how we show up for each other. Reports to: Manager, Product Research Location: Remote, US Compensation Range: $200,000 to $230,000 base plus bonus and equity What You’ll Do: The Huntress Product Research team has the unique honor of waking up every morning knowing we’re going to make hackers regret targeting our partners and customers. As a Principal Product Researcher, we’re looking for someone who wants to pour all of their creativity into building and implementing simple solutions that are disproportionately effective at countering these constantly evolving threats. Competitive candidates have experience managing, deploying, and securing SMB environments utilizing a wide variety of security software, best practices, and automation tools. Familiarity with product management, incident response, social engineering, psychology, education, and managed service provider tools is an additional way to differentiate yourself. As you can imagine, success doesn’t happen in a vacuum. An effective Product Researcher fosters highly collaborative environments between the Product, Engineering, and Security teams to accelerate our mission and secure the 99% of businesses that fall below the enterprise poverty line. This collaboration is needed to produce and prioritize a unified technical vision that ultimately delivers our most impactful features and capabilities. We defend over 5M endpoints for 225,000+ mid-sized and small-business customers, and that number continues to grow each month. Given this market’s tighter budget, it’s not financially feasible to assign human analysts to each client. The Security Operations team addresses this challenge head-on by building and scaling highly automated efficiencies—often lightly augmented by our SOC — that make intruders earn every inch of their access while maintaining affordability and healthy gross margins. Roles and Responsibilities: Identify innovative ways to detect Windows OS threats Develop cross-platform features that leverage telemetry from common OS subsystems such as file system, memory, process, and network activity Research and development of sensor capabilities to provide visibility and detection support for attack techniques across supported Windows OS versions Work collaboratively with internal engineering and detection teams to implement detection logic Identify and evaluate new telemetry opportunities Identify and address gaps in product coverage Respond to product escalations Perform False Positive and False Negative investigations Lead product research initiatives to develop and evaluate security product strategies and technologies Coordinate with Product and Engineering teams to integrate and operationalize solutions developed by Threat Operations teams Applies AI as a practical part of day-to-day product research work to improve the speed, quality, and impact of research outputs Uses AI to support information gathering, analysis, prototyping, and production of clear, decision-useful work products while maintaining accountability for the final output Builds and reuses lightweight prompts, templates, or workflows for recurring research tasks rather than relying on one-off use Develop internal and external technical documentation to educate customers and communicate research findings to adjacent teams about security risks and opportunities Mentor and teach technical expertise to advance the broader community Promote Huntress’ reputation through media interaction, public speaking, CFPs, CTFs, and blogs Qualifications: Expert in Windows OS internals, components, APIs, and design Prior experience with Windows OS kernel coding and device drivers Experience testing EDRs, bypasses, and evasion techniques Comfortable with reverse engineering and using debuggers Proficiency in multiple programming/scripting languages, such as C/C++/C#, PowerShell, and Python Applies AI to improve research quality, speed, and outputs in day-to-day work Commitment to clear documentation of research findings Experience with MITRE ATT&CK matrix, SIGMA, Yara, and Elasticsearch/Kibana What We Offer: 100% remote work environment - since our founding in 2015 Generous paid time off policy, including vacation, sick time, and paid holidays 12 weeks of paid parental leave Highly competitive and comprehensive medical, dental, and vision benefits plans 401(k) with a 5% contribution regardless of employee contribution Life and Disability insurance plans Stock options for all full-time employees One-time $500 reimbursement for building/upgrading home office Annual allowance for education and professional development assistance $75 USD/month digital reimbursement Access to the BetterUp platform for coaching, personal, and professional growth Huntress is committed to creating a culture of inclusivity where every single member of our team is valued, has a voice, and is empowered to come to work every day just as they are. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, disability, veteran status, genetic information, marital status, or any other legally protected status. We do discriminate against hackers who try to exploit businesses of all sizes. Accommodations: If you require reasonable accommodation to complete this application, interview, or pre-employment testing or participate in the employee selection process, please direct your inquiries to accommodations@huntresslabs.com . Please note that non-accommodation requests to this inbox will not receive a response. Huntress uses artificial intelligence tools to assist in reviewing and evaluating job applications, including resume screening, skills assessment, and candidate matching and comparisons. These AI tools support our human recruiters in the initial review process, but do not make final hiring decisions without human involvement. By submitting your application, you acknowledge this use of AI in our recruitment process. Please review our Candidate Privacy Notice for more details on our practices and your data privacy rights. #BI-Remote

Location: San Francisco, CA 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 team Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries. The team combines cutting-edge AI with hands-on biological research, positioning Anthropic at the forefront of AI-accelerated scientific discovery. About the role We're seeking an exceptional Research Scientist to join the team. This role combines deep computational biology expertise with frontier AI capabilities, positioning Anthropic at the forefront of AI-driven scientific discovery. As one of the first computational members of this Life Sciences research group, you'll work on a high-impact team that operates at the intersection of computational and experimental biology. You'll bring broad computational biology experience to bear across the team's projects, driving discoveries from large-scale computational analysis of biological data through to results our experimental scientists can test, and moving flexibly between problems as the science demands. You'll have substantial access to Claude and you'll help establish how computational biology operates at Anthropic. This role offers a unique opportunity to shape how AI transforms biological research. You'll work with some of the world's best AI researchers while tackling problems that matter deeply for scientific understanding and biomedicine. If you're excited about using your computational expertise to make fundamental biological discoveries and guide the development of transformative AI systems, we want to hear from you. Key responsibilities Build, run, and maintain the analysis pipelines that back the team's experimental programs: sequence analysis at petabyte scale, structural bioinformatics, phylogenetic and comparative genomics, design and analysis of high-throughput functional screens, biological sequence modeling, etc. Partner directly with experimental biologists to design experiments that produce high-quality data, and turn results around fast enough to immediately inform the next experiment Draw on the literature and curated biological knowledge bases alongside primary data to generate and prioritize hypotheses for experimental follow-up Stand up and maintain the team's computational infrastructure: data ingestion, workflow orchestration, internal databases, and the interfaces that make all of it accessible to both researchers and AI agents Use Claude and our internal agent frameworks heavily in your own work, and feed what you learn back to the model-improvement and product teams as evaluations, datasets, and concrete failure cases Pick up analyses across projects as priorities shift; we're looking for breadth and flexibility over a single deep specialty Minimum qualifications Have a PhD in computational biology, bioinformatics, genomics, biophysics, machine learning, computer science, or a related quantitative or biological field, or equivalent industry research experience Have a track record of computational biology research you have led end to end, from question to result, with evidence of impact (for example publications, preprints, released datasets or tools, or research that changed a program's direction) Have demonstrated breadth across multiple areas of computational biology Are proficient in one or more programming languages used in scientific computing and comfortable working on large datasets in Linux and cloud compute environments Can take an ambiguous biological question, scope the analysis, and produce a result an experimentalist can act on Communicate computational results clearly to both biologists and ML researchers Preferred qualifications Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments Are results-oriented, with a bias towards flexibility and impact Hands-on experience in experimental biology, or a track record of designing experiments side by side with experimentalists Experience building tools, pipelines, or agentic systems on top of LLMs, or training models on biological sequence data Deep expertise in one or two areas of computational biology (for example structural biology, metagenomics, single-cell genomics, or protein design) on top of the required breadth The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. But 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. 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.