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Location: Yerevan, Armenia Description Digitain is looking for Data Protection Officer (DPO) to join its Legal Directorate. In this role, you will play a key part in ensuring that Digitain’s data processing activities and privacy practices comply with the highest legal, regulatory, and ethical standards. You will support the company in maintaining robust data protection measures across all jurisdictions where Digitain operates. Responsibilities Monitor, review, and advise on Digitain’s data protection policies, practices, and procedures Provide guidance on compliance with data protection laws and regulations, including GDPR and other applicable legislation Advise management and internal teams on data privacy risks, mitigation strategies, and recommended actions Ensure proper handling of data subject requests, including access, correction, and deletion requests Perform legal research and analysis on international, regional, and local data protection laws Collaborate with internal departments to facilitate lawful cross-border data transfers Maintain records, documentation, and reporting in line with internal policies and legal requirements Undertake other tasks and projects as assigned to meet business objectives Requirements LL.B. or LL.M. degree in Law, or relevant legal qualification Minimum 6-9 years of experience in data protection, privacy law, or related legal/compliance roles Strong knowledge of GDPR, local data protection laws, and international privacy frameworks Proven experience in data protection risk assessments, audits, and privacy compliance programs Completion of recognized data privacy certifications or courses, such as: Certified Information Privacy Professional (CIPP/E or CIPP/A) Certified Information Privacy Manager (CIPM) Other relevant GDPR or data privacy training programs Fluency in written and spoken English and Russian Excellent analytical, drafting, and problem-solving skills with strong attention to detail Strong organizational and time-management abilities with the ability to handle multiple priorities Excellent interpersonal and communication skills, with the ability to advise and collaborate across teams Proactive, self-motivated, and capable of operating under pressure

Location: Lagos, Nigeria; Beograd, Serbia; Limassol, Cyprus; Belarus; Moscow, Russia We’re looking for a Head of Product (Digital Collection) to shape and scale our digital collection ecosystem - from strategy and analytics to automation and technology. Your mission will be to build data-driven tools, optimize collection processes, and enhance recovery efficiency through smart products and innovation. Key Responsibilities: Develop, implement, evaluate, and continuously optimize collection strategies, tools, methods, and analytical models. Define and manage key KPIs for the collection department to ensure sustainable portfolio growth and operational efficiency. Identify growth opportunities, design and run pilot projects, test and implement new strategies. Drive process automation across collection operations — manage, assess, and modernize technical systems, including telephony and robotic solutions. Deploy and refine collection scoring models to improve segmentation and recovery outcomes. Collaborate with external vendors and technology partners to identify, integrate, and implement innovative solutions. Analyze key performance indicators for collection and pre-collection, monitor delinquency trends, and identify deviations and growth points. Automate analytics and reporting, manage the KPI system, and oversee team performance evaluation and motivation within the collection department. Requirements 3+ years of experience in a similar leadership role within a bank, microfinance organization, or collection agency. Proven experience in designing, launching, and optimizing business processes in the debt collection domain. Experience implementing and maintaining automated collection systems (including configuration of robotic tools and telephony). Strong technical acumen: understanding of APIs, system integrations, backlog management, and task prioritization. Solid SQL knowledge and ability to work with databases to analyze and optimize collection strategies. Data-driven and systematic approach to collection management — capable of translating ideas into measurable results and vice versa. Benefits Opportunity: The opportunity to work in an innovative fintech company with a global reach Benefits: Competitive salary, paid vacations and additional day-offs Growth Potential: Accelerating your product leadership career in a high-growth, innovation-driven fintech. Purpose: Build tools that empower thousands of clients to thrive and suceed.

Location: San Francisco, CA | New York City, NY | Seattle, WA; Washington, DC 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 At Anthropic, we are pioneering new frontiers in AI that have the potential to greatly benefit society. However, developing advanced AI also comes with risks if not properly safeguarded. That's why we are seeking an exceptional Detection and Response engineer that will be on the frontlines to build solutions to monitor for threats, rapidly investigate incidents, and coordinate response efforts with other teams. In this role, you will have the opportunity to shape our security capabilities from the ground up alongside our world-class research and security teams. Responsibilities: Lead cybersecurity Incident Response efforts covering diverse domains from external attacks to insider threats involving all layers of Anthropic’s technology stack Develop and deploy novel tooling that may leverage Large Language Models to enhance detection, investigation, and response capabilities Create and optimize detections, playbooks, and workflows to quickly identify and respond to potential incidents Review Incident Response metrics and procedures and drive continuous improvement Work cross functionally with other security and engineering teams Note: This position will require participation in an on-call rotation You may be a good fit if you: 3+ years of software engineering experience, with security experience a plus and/or 5+ years of detection engineering, incident response, or threat hunting experience A solid understanding of cloud environments and operations Experience working with engineering teams in a SaaS environment Exceptional communication and collaboration skills An ability to lead projects with little guidance The ability to pick up new languages and technologies quickly Experience handling security incidents and investigating anomalies as part of a team Knowledge of EDR, SIEM, SOAR, or related security tools Strong candidates may also have experience with: Experience performing security operations or investigations involving large-scale Kubernetes environments A high level of proficiency in Python and query languages such as SQL Experience analyzing attack behavior and prototyping high quality detections Experience with threat intelligence, malware analysis, infrastructure as code, detection engineering, or forensics Experience contributing to a high growth startup environment Deadline to apply: None. Applications will be reviewed on a rolling basis. 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 — $405,000 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. 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: Poland; Ukraine; Georgia Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. What you will do - Deliver end-to-end data science projects using classical machine learning (e.g., regression, classification, time series forecasting) and deep learning approaches — from data exploration and modeling to deployment and performance tracking. - Collaborate closely with business stakeholders to identify opportunities and translate them into measurable data-driven solutions. - Present complex analytical findings in a clear, actionable way to both technical and non-technical audiences. - Contribute to analytical planning and ensure alignment with overall business objectives. - Support presales activities by preparing data/ML solution concepts, participating in client meetings, and estimating project scope and potential value. - Help shape the Data Science practice by contributing to its strategic development and supporting recruitment initiatives. What you bring - Proven experience as a Data Scientist delivering end-to-end projects — from exploratory data analysis to model deployment, performance evaluation, and experimentation (e.g., A/B testing). - Strong expertise in working with tabular and time-series data, including EDA, feature engineering, predictive modeling, and model evaluation. - Proficiency in Python and common data-science libraries (e.g., pandas, scikit-learn, TensorFlow/PyTorch). - Experience leading or mentoring analytics teams and coordinating with business stakeholders. - Excellent communication skills, able to translate between technical and business perspectives effectively. - Solid understanding of business processes and data structures. - Confidence in client-facing settings: gathering requirements, shaping analytical roadmaps, and delivering measurable business value. - Fluency in English for meetings with international clients. Nice to have - Hands-on experience with deep learning, computer vision, or generative AI projects. - Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps tools. - Experience with data visualization or BI tools for communicating insights. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: Dhahran, Saudi Arabia; Mumbai, India; Delhi, India Eram Talent is actively seeking a knowledgeable and experienced Project Engineer (EPC) to join our team for a prominent company within the Engineering, Procurement, and Construction (EPC) sector. The ideal candidate will be responsible for managing and overseeing projects through all phases of the EPC process. This role will involve ensuring that projects are delivered on time, within budget, and in compliance with quality and safety standards. As part of ERAM Group, E-Talent is an independent Talent Acquisition Consultancy committed to connecting top-tier professionals with outstanding opportunities across various domains including Engineering, Oil & Gas, Infrastructure, and Construction. This is an exciting opportunity for an ambitious engineer to drive impactful projects within a dynamic environment. Responsibilities 1. Technology and Engineering Management 1.1 Assist the Project Manager in reviewing project basic engineering design documents, ensuring full compliance with Saudi Aramco design standards (e.g., SAES, SAMSS, SABP) and project specifications. 1.2 Coordinate design work across various disciplines (Process, Piping, Mechanical, Electrical, Instrumentation, Civil, etc.), chair or participate in key technical coordination meetings, and resolve interface conflicts and technical challenges during the design phase. 1.3 Manage the flow, approval, and archiving of project technical documents, ensuring the accuracy and completeness of all engineering deliverables. 1.4 Lead or participate in the technical evaluation of Technical Queries (TQs), Material Substitution Requests (SRM), and Change Requests (CRs), and follow up on the Saudi Aramco approval process. 2. Procurement and Supplier Coordination 2.1 Provide technical support to assist in the preparation of procurement technical specifications for key equipment and materials. 2.2 Participate in the technical bid evaluation of key suppliers. 2.3 Review technical documents submitted by suppliers (such as drawings, data sheets, calculation reports, ITP), ensuring they meet project requirements. 2.4 Coordinate the resolution of any technical issues arising during equipment manufacturing. 3. Construction and Pre-Commissioning Support 3.1 Provide comprehensive technical support to field construction, resolving technical challenges encountered during construction. 3.2 Review the technical feasibility of Construction Method Statements. 3.3 Manage engineering changes within the project scope, assess the impact of changes on cost, schedule, and technology, and strictly adhere to the change management process. 3.4 Participate in onsite system Mechanical Completion checks, ensuring installation work conforms to design intent and specifications. 3.5 Support pre-commissioning and commissioning activities by providing necessary technical documents and guidance. 4. Planning, Scheduling, and Reporting 4.1 Assist the Project Manager in developing and controlling the project's engineering schedule. 4.2 Prepare and submit weekly/monthly engineering technical progress reports to the Project Manager and the client (Saudi Aramco). 4.3 Identify and assess project technical risks and propose mitigation measures. 5. Compliance and Standards 5.1 Ensure all engineering activities strictly comply with Saudi Aramco's Health, Safety, and Environment (HSE) policies and procedures. 5.2 Ensure the entire project process conforms to Saudi Aramco's Quality Management System requirements. 6. Communication and Coordination 6.1 Act as one of the primary points of contact for daily technical communication with the client's (Saudi Aramco) engineers. 6.2 Effectively coordinate work between the internal design team, procurement team, construction team, and subcontractors. Requirements 1. Education and Professional Qualifications Bachelor's degree or higher, majoring in Petroleum Engineering, Chemical Engineering, Mechanical Engineering, or a related engineering field. Possession of PMP (Project Management Professional), Chartered Engineer, or equivalent certification is preferred. 2. Work Experience 2.1 Minimum 8-10 years of project engineering experience in the oil, gas, or petrochemical industry, including at least 5 years in a Project Engineer or similar technical coordination role on large-scale Saudi Aramco petrochemical EPC projects. In-depth understanding and practical experience with Saudi Aramco standards, processes, and culture are required. 2.2 Project experience in oil-gas separation, production enhancement, gathering and distribution stations, or similar upstream/midstream facilities is preferred. 3. Knowledge and Skills 3.1 Proficiency in at least one core engineering discipline (e.g., Process, Piping, or Mechanical) and familiarity with the fundamentals of other related disciplines. 3.2 Thorough understanding of the project lifecycle, from conceptual design to mechanical completion and commissioning. 3.3 Familiarity with international engineering standards (e.g., ASME, API, ANSI, IEC) and Saudi Aramco-specific standards. 3.4 Proficient in MS Office (especially Word, Excel, PowerPoint). 3.5 Proficient in project management software (e.g., Primavera P6 or MS Project). 3.6 Familiarity with common engineering design software and document management systems (e.g., SPF, Aconex). 3.7 Fluent in both English and Arabic, with both languages serving as working languages. 4. Core Competencies and Personal Attributes 4.1 Ability to communicate clearly and effectively with technical experts, management, and clients. 4.2 Ability to analyze complex problems under pressure and propose practical solutions. 4.3 Ability to lead cross-functional teams in resolving technical issues, even in the absence of direct reporting lines. 4.4 Capable of managing multiple tasks and large volumes of technical information simultaneously. 4.5 Adaptability to fast-paced, high-demand project environments, and ability to navigate cultural differences and work challenges. 4.6 Strong sense of responsibility and commitment to achieving project goals. Benefits Job Location: Ningbo, China & Saudi Haradh Contract Period: 1 to 3 years depending on the project and performance. Visa: Business visa will be provided by the Client.

Location: San Francisco, CA | New York City, NY; San Francisco, CA | New York City, NY | Seattle, WA 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 research teams are pushing the boundaries of AI safety and capability research, and they need exceptional tools to do their best work. As a Software Engineer on the Research Tools team, you'll build the infrastructure and applications that enable our researchers to iterate quickly, run complex experiments, and extract insights from frontier AI systems. This role sits at the intersection of product thinking and full-stack engineering. You'll work directly with researchers and engineers to deeply understand their workflows, identify bottlenecks, and rapidly ship solutions that multiply their productivity. Whether you're building human feedback interfaces for model evaluation, creating platforms for experiment orchestration, or developing novel visualization tools for understanding model behavior, your work will directly accelerate our mission to build safe, reliable AI systems. We're looking for someone who can operate with high agency in an ambiguous environment—someone who can be dropped into a research team, quickly develop domain expertise, and independently drive impactful projects from conception to delivery. No ML or Research experience is required Responsibilities Build and maintain full-stack applications and infrastructure that researchers use daily to conduct experiments, collect feedback, and analyze results Partner closely with research teams to understand their workflows, pain points, and requirements, translating these into technical solutions Design intuitive interfaces and abstractions that make complex research tasks accessible and efficient Create reusable platforms and tools that accelerate the development of new research applications Rapidly prototype and iterate on solutions, gathering feedback from users and refining based on real-world usage Take ownership of complete product areas, from understanding user needs through design, implementation, and ongoing iteration Contribute to technical strategy and architectural decisions for research tooling Mentor other engineers and help establish best practices for research application development You may be a good fit if you Have 5+ years of software engineering experience with a strong focus on full-stack development Excel at rapid iteration and shipping—you can move from concept to working prototype quickly Have experience building tools, platforms, or infrastructure for technical users (engineers, researchers, data scientists, analysts, etc.) Demonstrate high agency and ability to operate independently in ambiguous environments Can quickly develop deep understanding of complex technical domains Have strong product instincts and can identify the right problems to solve Are proficient with modern web technologies (React, TypeScript, Python, etc.) Have a track record of building user-facing applications that are actually used and loved by their target audience Communicate effectively with both technical and non-technical stakeholders Care about the societal impacts of your work and are motivated by Anthropic's mission Strong candidates may also have Experience building research tools, scientific software, or experimentation platforms Background in machine learning, AI research, or working closely with ML researchers Founded or been an early engineer at a startup, particularly one focused on developer or researcher tools Built open-source tools or platforms with active user communities Experience with data visualization, interactive interfaces, or novel interaction paradigms Contributed to engineering platforms or internal tooling at scale (similar to Heroku, Vercel, or other platform-as-a-service products) Experience leveraging AI/LLMs to build more powerful or efficient tools Previous work in creative tools, artist tools, or other domains requiring deep user empathy Domain knowledge in areas like human-computer interaction, systems safety, or AI alignment Representative projects Building interfaces for collecting and managing human feedback on model outputs at scale Creating experiment orchestration platforms that make it easy to launch, monitor, and analyze complex research runs Developing visualization tools that help researchers understand model behavior and identify failure modes Designing reusable components and frameworks that enable rapid development of new research applications Building sandboxed execution environments for safely running AI-generated code 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 — $405,000 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. 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: Rome, Italy; Lisbon, Portugal; Berlin, Germany; Paris, France; Madrid, Spain Müller's Solutions is looking for an enthusiastic BMC Helix Support / Technical Support Analyst to join our remote team. In this vital role, you will deliver superior technical support to our clients using BMC Helix, assisting them with troubleshooting and resolving various technical challenges related to the software. This position requires a proactive approach in providing solutions while ensuring a high level of customer satisfaction. Key Responsibilities: Provide efficient first-level technical assistance to clients using BMC Helix, addressing and resolving inquiries promptly. Troubleshoot issues related to BMC Helix, including installation, configuration, and operational challenges. Guide clients through the implementation process, ensuring effective usage of the BMC Helix platform. Document technical problems and solutions systematically to build a robust knowledge base for future reference. Collaborate with product teams to communicate customer feedback and assist in routine software updates. Participate in training sessions and webinars to educate users on best practices within the BMC Helix environment. Contribute to process improvement initiatives that enhance customer support experiences. Requirements Requirements: Bachelor's degree in Computer Science, Information Technology, or related discipline. Minimum of 2 years of technical support experience, ideally within a software or IT service environment. In-depth knowledge of BMC Helix and experience with ticketing systems. Strong analytical and troubleshooting skills, with attention to detail. Excellent verbal and written communication abilities to convey complex information clearly. Ability to work independently in a remote setup while managing efficiency and productivity. Customer-oriented mindset with a dedication to exceeding client expectations. Preferred Qualifications: Experience in ITIL frameworks or IT service management processes. Familiarity with other IT service management tools and methodologies. Prior experience in a remote technical support role. Relevant certifications in BMC Helix or IT support services are a plus. Capability to prioritize tasks effectively and work under minimal supervision.

Location: Rome, Italy; Lisbon, Portugal; Berlin, Germany; Paris, France; Madrid, Spain Müller's Solutions is looking for a talented BMC Helix Integration / Automation Specialist to join our dynamic team remotely. In this pivotal role, you will be tasked with creating and implementing automation solutions using BMC Helix integration tools. Your contributions will be essential in streamlining operations and enhancing client satisfaction through effective integration strategies. Key Responsibilities: Develop and implement integration solutions utilizing BMC Helix to facilitate smooth data exchanges across various applications. Create automation workflows aimed at improving operational efficiencies and reducing manual tasks. Engage with clients to understand their unique requirements and translate these into technical specifications for integration. Perform ongoing monitoring and troubleshooting of integration systems to ensure continuous improvement and reliability. Document and maintain detailed records of integration processes, workflows, and operational guidelines. Keep abreast of new features and best practices related to BMC Helix and integration technologies. Requirements Qualifications: Bachelor's degree in Computer Science, Information Technology, or a related discipline. 3+ years of experience in integration or automation roles, specifically with BMC Helix. Comprehensive understanding of integration frameworks, methodologies, and tools. Proven experience in creating automation scripts and workflows. Proficiency in programming languages such as Python, Java, or equivalent. Familiarity with RESTful APIs, web services, and data exchange protocols. Strong analytical, troubleshooting, and problem-solving capabilities. Exceptional communication skills to collaborate effectively with clients and team members. A self-starter who can work independently and manage multiple tasks effectively in a remote setting. Experience with cloud services and platforms is advantageous.

Location: New York; San Francisco; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Our team is a fast-growing group of committed researchers and engineers. The mission of the team is to build reliable machine learning systems and optimize audio inference serving efficiency using innovative techniques. As an engineer on this team, you will work on advancing core audio model serving metrics, including latency, throughput, and quality by diving deep into our systems, identifying bottlenecks, and delivering creative solutions for audio processing and streaming workloads. You’ll collaborate closely with both the training and serving infrastructure teams to ensure seamless integration between model development and deployment, with a special focus on real-time and streaming audio inference. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Qualifications: - Significant experience developing high-performance audio or machine learning inference systems. - Proficiency with programming languages such as C++ and Python. - Hands-on experience with deep learning models for audio, speech, or language applications. - A bias for action and a strong results-oriented mindset. It is a big plus if you also have considerable experience with: - GPU programming, low-level system optimization, model parallelization techniques over multiple GPUs - Have experience with duplex real-time streaming architectures. - Internals of machine learning frameworks for audio (such as PyTorch, TensorFlow, or specialized audio libraries). - Have experience with inference framework like vLLM, SGLang, Tensort-LLM, or custom distributed inference systems - Sequence modeling (e.g., transformers for audio/speech) and end-to-end audio pipeline optimization Working location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: New York; San Francisco; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: - model architecture and MoE routing optimization - decoding and inference-time algorithm improvements - software/hardware co-design for GPU acceleration - performance optimization without compromising model quality Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Key Responsibilities: As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production. Qualifications: - Have a PhD in Machine Learning or a related field - Understand LLM architecture, and how to optimize LLM inference given resource constraints - Have significant experience with one or more techniques that enhance model efficiency - Strong software engineering skills - An appetite to work in a fast-paced high-ambiguity start-up environment - Publications at top-tier conferences and venues (ICLR, ACL, NeurIPS) - Passion to mentor others Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: New York; San Francisco; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Job Responsibilities: As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. Qualifications: - 5+ years of experience writing high-performance, production-quality code - Strong programming skills in C++ or Python (Rust/Go also welcome) - Experience working with large language models and familiarity with the LLM inference ecosystem (e.g., vLLM, SGLang, etc.) - Ability to diagnose and resolve performance bottlenecks across the model execution stack - A strong bias for action — you ship fast, measure impact, and iterate It’s a big plus if you have experience with: - GPU programming, CUDA, or low-level systems optimization - Language modeling with transformers (MoE, speculative decoding, KV-cache optimizations) - Scaling performance-critical distributed systems (e.g., computation, search, storage) Working Location: This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

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 role: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks using “microscopes” we build, or as treating neural networks as binary computer programs we're trying to "reverse engineer". A few places to learn more about our work and team at a high level are this introduction to Interpretability from our research lead, Chris Olah ; a discussion of our work on the Hard Fork podcast produced by the New York Times, and this blog post (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results. Some of our team's notable publications include A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , Toy Models of Superposition , Scaling Monosemanticity , and our Circuits’ Methods and Biology papers. This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , Activation Atlases , and Building Blocks . We aim to create a solid foundation for mechanistically understanding neural networks and making them safe (see our vision post ). In the short term, we have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work found millions of features in Sonnet, one of our production language models, represents progress in this direction. In our most recent work, we develop methods that allow us to build circuits using features and use this circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks. We often collaborate with teams across Anthropic, such as Alignment Science and Societal Impacts to use our work to make Anthropic’s models safer. We also have an Interpretability Architectures project that involves collaborating with Pretraining. Responsibilities: Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights Design and run robust experiments, both quickly in toy scenarios and at scale in large models Create and analyze new interpretability features and circuits to better understand how models work. Build infrastructure for running experiments and visualizing results Work with colleagues to communicate results internally and publicly You may be a good fit if you: Have a strong track record of scientific research (in any field), and have done some work on Interpretability Enjoy team science – working collaboratively to make big discoveries Are comfortable with messy experimental science. We're inventing the field as we work, and the first textbook is years away You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results You can clearly articulate and discuss the motivations behind your work, and teach us about what you've learned. You like writing up and communicating your results, even when they're null To learn more about the skills we look for and how to prepare for this role, see our blog post – So You Want to Work in Mechanistic Interpretability? Familiarity with Python is required for this role. Role Specific Location Policy: This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis. 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 — $850,000 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. 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: 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. Note: we don't have open Research Manager positions on the Interpretability team at this time. However, we're actively growing our team of Research Engineers and Research Scientists . If you're excited about interpretability research and open to an individual contributor role, we encourage you to apply. About the Interpretability team When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team’s mission is to reverse engineer how trained models work, and Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that a mechanistic understanding is the most robust way to make advanced systems safe. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks, or as treating neural networks as binary computer programs we're trying to "reverse engineer". We aim to create a solid scientific foundation for mechanistically understanding neural networks and making them safe (see our vision post ). We have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work which found millions of features in Claude 3.0 Sonnet, one of our production language models, represents progress in this direction. In our most recent work , we developed methods that allow us to build circuits using features and use these circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Claude Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks. A few places to learn more about our work and team are this introduction to Interpretability from our research lead, Chris Olah, Stanford CS25 lecture given by Josh Batson, and TWIML AI podcast with Emmanuel Ameisen. Some of our team's notable publications include and our Circuits’ Methods and Biology papers, Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet , Towards Monosemanticity: Decomposing Language Models With Dictionary Learning , A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , and Toy Models of Superposition . This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , Activation Atlases , and Building Blocks . About the role As a manager on the Interpretability team, you'll support a team of expert researchers and engineers who are trying to understand at a deep, mechanistic level, how modern large language models work internally. Few things can accelerate this work more than great managers. Your work as manager will be critical in making sure that our fast-growing team is able to meet its ambitious safety research goals over the coming years. In this role, you will partner closely with an individual contributor research lead to drive the team's success, translating cutting-edge research ideas into tangible goals and overseeing their execution. You will manage team execution, careers and performance, facilitate relationships within and across teams, and drive the hiring pipeline. If you're more interested in making individual direct technical contributions to our research as the primary focus of your role, feel free to apply to our Research Scientist or Research Engineer roles instead. Key responsibilities Partner with a research lead on direction, project planning and execution, hiring, and people development Set and maintain a high bar for execution speed and quality, including identifying improvements to processes that help the team operate effectively Coach and support team members to have more impact and develop in their careers Drive the team's recruiting efforts, including hiring planning, process improvements, and sourcing and closing Help identify and support opportunities for collaboration with other teams across Anthropic Communicate team updates and results to other teams and leadership Maintain a deep understanding of the team's technical work and its implications for AI safety You may be a good fit if you Are an experienced manager (minimum 2-5 years) with a track record of effectively leading highly technical research and/or engineering teams Have a background in machine learning, AI, or a related technical field Actively enjoy people management and are experienced with coaching and mentorship, performance evaluation, career development, and hiring for technical roles Have strong project management skills, including prioritization and cross-functional coordination and collaboration Have managed technical teams through periods of ambiguity and change Are a quick learner, capable of understanding and contributing to discussions on complex technical topics and are motivated to learn about our research Are a strong communicator both in speaking and in writing Believe that advanced AI systems could have a transformative effect on the world, and are passionate about helping make sure that transformation goes well Strong candidates may also have Experience scaling engineering infrastructure Experience working on open-ended, exploratory research agendas aimed at foundational insights Some familiarity with our work and mechanistic interpretability Role-Specific Location Policy This role is expected to be in our SF office for 3 days a week. 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. 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: 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 role: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs. More resources to learn about our work: Our research blog - covering advances including Monosemantic Features and Circuits An Introduction to Interpretability from our research lead, Chris Olah The Urgency of Interpretability from CEO Dario Amodei Engineering Challenges Scaling Interpretability - directly relevant to this role 60 Minutes segment - Around 8:07, see a demo of tooling our team built New Yorker article - what it's like to work on one of AI's hardest open problems Even if you haven’t worked on interpretability before, the infrastructure expertise is similar to what's needed across the lifecycle of a production language model: Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model's internal activations mid-forward-pass - for example, adding a "steering vector" Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are focused on finding bottlenecks, fixing them and moving ahead given rapidly evolving research and safety mission The science keeps scaling - and it's now applied directly in safety audits on frontier models, with real deadlines. As our research has matured, engineering and infrastructure have become a bottleneck. Your work will have a direct impact on one of the most important open problems in AI. Responsibilities: Build and maintain the specialized inference and training infrastructure that powers interpretability research - including instrumented forward/backward passes, activation extraction, and steering vector application Resolve scaling and efficiency bottlenecks through profiling, optimization, and close collaboration with peer infrastructure teams Design tools, abstractions, and platforms that enable researchers to rapidly experiment without hitting engineering barriers Help bring interpretability research into production safety audits - with real deadlines and high reliability expectations Work across the stack - from model internals and accelerator-level optimization to user-facing research tooling You may be a good fit if you: Have 5-10+ years of experience building software Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python Are extremely curious about unfamiliar domains; can quickly learn and put that knowledge to work, e.g. diving into new layers of the stack to find bottlenecks Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions Prefer fast-moving collaborative projects to extensive solo efforts Are curious about interpretability research and its role in AI safety (though no research experience is required!) Care about the societal impacts and ethics of your work Are comfortable working closely with researchers, translating research needs into engineering solutions. Strong candidates may also have experience with: Optimizing the performance of large-scale distributed systems Language modeling fundamentals with transformers High Performance LLM optimization: memory management, compute efficiency, parallelism strategies, inference throughput optimization Working hands-on in a mainstream ML stack - PyTorch/CUDA on GPUs or JAX/XLA on TPUs Collaborating closely with researchers and building tooling to support research teams; or directly performed research with complex engineering challenges Representative Projects: Building Garcon , a tool that allows researchers to easily instrument LLMs to extract internal activations Designing and optimizing a pipeline to efficiently collect petabytes of transformer activations and shuffle them Profiling and optimizing ML training jobs, including multi-GPU parallelism and memory optimization Building a steered inference system that applies targeted interventions to model internals at scale (conceptually similar to Golden Gate Claude but for safety research) Role Specific Location Policy: This role is based in the San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis. 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: $315,000 — $560,000 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. 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: New York City, NY; San Francisco, CA; Seattle, WA 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 As a Product Support Specialist, you’ll be at the front lines of safely delivering AI to the world, providing high-touch support to the businesses building on Claude. You’ll take the cases that need more than a help article: understanding how a customer has built on our platform (their integrations, their authentication and identity setup, their use of the models) and then investigating, diagnosing, and resolving their most complex technical needs. You’ll partner with engineers to get to the bottom of things, and with account teams to keep the customer’s trust while you do. Additionally, you’ll help us identify and close gaps in our team’s technical knowledge, turning what you learn from each case into documentation, tooling, and product feedback so the whole team gets sharper. This is a role for someone who wants their technical depth to matter to real businesses, and who cares as much about how we systematically support customers at scale as about the case in front of them. Responsibilities Provide high-touch support to our most strategic customers, communicating clearly and empathetically with a wide range of user personas, context-switching between guiding an executive through an incident and providing critical product knowledge to an admin in need of help within the same hour Serve as an escalation point for our most complex technical issues: reproducing customer issues, utilizing logs and traces, and providing solutions alongside engineers Troubleshoot SSO, SAML, and OAuth authentication flows, and the integration surface where our products meet a customer’s infrastructure Partner with engineers, teammates, and other internal stakeholders to diagnose and resolve user issues, both individually and at scale Manage on-call tasks for high-urgency user issues with extreme ownership Respond to user support cases with a variety of complexity, from questions from individuals to complex API debugging for large businesses Become an expert in all Anthropic products, and delight in the hunt when something doesn’t behave as expected Uplevel our team’s technical knowledge by scoping gaps, working with cross-functional partners to deeply understand relevant nuances, and building resources that grow with our products Suggest and drive improvements to increase user satisfaction through support processes, as well as own initiatives that increase efficiency and drive down contact rates Operate in ambiguity, making informed decisions even in never-before-seen situations Prioritize critically and comfortably adapt to an ever-evolving product landscape Minimum qualifications Several years of technical product support experience at a high-growth tech company, including hands-on API debugging, ideally on a tier-two, escalated, or priority support team Experience supporting enterprise or strategic accounts: exec-level communication, escalation management, and working shoulder-to-shoulder with account and engineering teams Fluency with APIs and technical SaaS products; you read technical docs with ease and can reason about someone else’s architecture from a handful of clues Experience troubleshooting SSO, SAML, and OAuth authentication flows A demonstrated ability to thrive in fast-paced, reactive situations while hitting core support metrics (CSAT, SLA, and the like) Strong user empathy and mastery of the support case lifecycle; you read between the lines, get to the heart of the need, and resolve it fast Crisp but kind written communication and a deep care for detail Persistence and curiosity: you’re energized by tracking down a bug, and more energized by fixing it for every similar user going forward A deep sense of ownership, genuine interest in Anthropic’s products, and enthusiasm for helping build the team Preferred qualifications While not required, we're particularly excited about candidates with one or more of these specializations: Comfort with command line interfaces and basic scripting (Bash, Python, JavaScript) SQL proficiency for querying logs and investigating issues Understanding of LLM capabilities, practical applications, and current limitations Familiarity with enterprise networking concepts and IT infrastructure Familiarity with Git workflows and version control concepts Experience supporting government or public sector customers, including compliance requirements and security frameworks Background in team lead roles or managing contract/vendor support teams We’re hiring across a range of experience levels to build depth in both technical capabilities and enterprise support. 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: $131,040 — $210,000 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. 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: Prague, Czechia D-ploy is an IT and Engineering Solutions company with operations throughout the EMEA region including Switzerland, Germany, Czech Republic, Austria, UK, as well as the USA. We pride ourselves on delivering innovative and superior services and solutions to numerous industry-leading clients. By building relationships and trusted partnerships within the IT community, we optimize our customer’s IT productivity and contribute to the organization’s success and value. We are interested in talking to engaging, flexible, and solution-oriented individuals who are looking to become a part of a dynamically growing and international organization. We are focused on creating value where IT counts, join us! Our ambition is to catalyse innovation capability by supporting priority teams to develop truly customer-centred products and services. We are developing an end-to end approach that provides design, design thinking, agile and lean approaches to product development. We are looking for a Talent Acquisition Coordinator (Spanish & Italian Speaking) to support our key projects designing innovation tools, training and experiences. ! This role lasts initially until the end of May 2026 with expected extension, where only a full-time cooperation is available as form of cooperation. Key Responsibilities Create and manage offer letters in local languages Initiate and monitor employment checks including drug and medical screenings, ensuring timely completion and escalation of discrepancies Complete and maintain all relevant documentation related to background checks or offer rescinds Handle sensitive candidate data in compliance with internal policies and confidentiality standards Coordinate communication between Talent Acquisition Business Partners, Hiring Managers, and candidates to ensure smooth pre-boarding processes Support administrative activities and contribute to the overall efficiency and compliance of the Global TA Coordination team Maintain accurate records and ensure alignment with company standards and timelines Requirements Minimum 1 year of coordination or administrative experience in Human Resources or Talent Acquisition Experience in pre-boarding processes such as contract generation, global mobility, or visa coordination is an advantage Familiarity with HR systems such as Workday preferred Strong attention to detail and accuracy in documentation and reporting Excellent organizational, problem-solving, and communication skills Proficiency in Microsoft Office, with advanced Excel skills preferred Ability to work effectively in a fast-paced, evolving, and remote environment Proven ability to manage multiple stakeholders and adapt to change University degree strongly preferred Fluency in English, Italian, and Spanish Candidates must declare Criminal record extract not older than three months Benefits Broad range of activities, tasks, and projects Flexible working conditions Minimum 5 weeks of vacation Paid sick days Meal vouchers Vouchers (B-day voucher, wedding, and new born surprise) Contributions to wellness programs (multisport card) Fishing for Friends program – our referral program Refreshments in the D-ploy office Further development and professional advancement Friendly and international working environment Company-sponsored events Competitive salary and various benefits Is IT in your DNA? If you believe you are a good match for this role, or any other opportunities for which D-ploy is currently staffing, then we are very keen to speak with you. You can apply though a variety of channels, including our website www.d-ploy.ch or by reaching our directly to our recruitment team recruiting@d-ploy.ch.

Location: Spain Pre-Sales Consultant will be responsible for advising our Business Development & Sales teams on large, complex deals addressing technical and product questions and helping the customer understand how to implement ProgressSoft’s systems most effectively. He will be responsible for being a product specialist with deep understanding of all product integrations and enterprise features. Responsibilities Work closely with sales/business development team to explore sales opportunities for company’s product suite. Liaise and discuss with customers/prospects to qualify the opportunity /lead and create a solution construct. Assist BD/ Sales team in the qualification of customer needs & performing pre demo needs analysis. Drive techno functional discussion in client interaction/pre-sales and appropriately capture customer requirement with maximum clarity. SPOC for complete pre-sales cycle from requirement scoping, product fitment, solutioning, and technical proposal creation by working closely with members of the sales, delivery, product & support team. Draft solution scope document which meets customer expectation and translate these accurately to the delivery team / product team for estimation and successful delivery mechanism. Generate product demo scripts & scenarios and orchestration of product demo/workshop. Manage, coordinate and execute complete bidding process of RFI and RFPs. Develop statement of work and other contractual documents as required. Complete any other tasks that may reasonably be required from time to time. Requirements Fluency in Spanish and English is a must. Self-Initiation and know-how-to-know skills. High level of performance. Outstanding leadership qualities and team building skills. Excellent communication capabilities. Creative problem-solving skills. Detail oriented and highly organized. Excellent follow-up skills. Bold travel schedule (up to 30%). Strong written and verbal communication skills to represent the company in a favorable manner. Highly motivated and able to influence and motivate others. Ability to work under pressure. Prepare SWOT analysis on solution offering and should be able to position company’s products against the competition in various geographies. Good knowledge of global real-time, rails, retail payments and payments landscape. Fair understanding of Real-time Payments globally including I PSD2, Open Banking, Payment Hub, SWIFT, SEPA. Hands on experience to preparing power point presentations, document and analysis report. Ability to initiate conversations and make a lasting impact. Should be regularly updated with the market knowledge on the payment domain and progress at various relevant geographies.

Location: Uzbekistan Pre-Sales Consultant will be responsible for advising our Business Development & Sales teams on large, complex deals addressing technical and product questions and helping the customer understand how to implement ProgressSoft’s systems most effectively. He will be responsible for being a product specialist with deep understanding of all product integrations and enterprise features. Responsibilities Work closely with sales/business development team to explore sales opportunities for company’s product suite. Liaise and discuss with customers/prospects to qualify the opportunity /lead and create a solution construct. Assist BD/ Sales team in the qualification of customer needs & performing pre demo needs analysis. Drive techno functional discussion in client interaction/pre-sales and appropriately capture customer requirement with maximum clarity. SPOC for complete pre-sales cycle from requirement scoping, product fitment, solutioning, and technical proposal creation by working closely with members of the sales, delivery, product & support team. Draft solution scope document which meets customer expectation and translate these accurately to the delivery team / product team for estimation and successful delivery mechanism. Generate product demo scripts & scenarios and orchestration of product demo/workshop. Manage, coordinate and execute complete bidding process of RFI and RFPs. Develop statement of work and other contractual documents as required. Complete any other tasks that may reasonably be required from time to time. Requirements Fluency in Russian and English is a must. Self-Initiation and know-how-to-know skills. High level of performance. Outstanding leadership qualities and team building skills. Excellent communication capabilities. Creative problem-solving skills. Detail oriented and highly organized. Excellent follow-up skills. Bold travel schedule (up to 30%). Strong written and verbal communication skills to represent the company in a favorable manner. Highly motivated and able to influence and motivate others. Ability to work under pressure. Prepare SWOT analysis on solution offering and should be able to position company’s products against the competition in various geographies. Good knowledge of global real-time, rails, retail payments and payments landscape. Fair understanding of Real-time Payments globally including I PSD2, Open Banking, Payment Hub, SWIFT, SEPA. Good knowledge of the CIS and Central Asian payments landscape is highly preferred. Hands on experience to preparing power point presentations, document and analysis report. Ability to initiate conversations and make a lasting impact. Should be regularly updated with the market knowledge on the payment domain and progress at various relevant geographies.