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In this role, you will lead accounting for a significant portion of Anthropic&#39;s owned infrastructure , network equipment, data center buildouts, and related capital assets underpinning our recently announced $50bn investment in American computing infrastructure.</p>\n<p>As we continue our rapid growth, you will help ensure the operational scalability and financial accuracy of the core functions that enable Anthropic&#39;s research and commercial success.</p>\n<p>This is an opportunity to be at the heart of one of the fastest-scaling companies in the industry, and to shape how Anthropic&#39;s growing fixed asset base is accounted for and understood across the business.</p>\n<p>You will own end-to-end accounting and set the strategy for scaling this function, working closely with cross-functional partners across Data Center Operations, Real Estate, Finance, and Legal. 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As a key member of our team, you&#39;ll take ownership of the training stack end-to-end, ensuring every GPU cycle drives scientific progress. Your goal is to make experimentation and training at Thinking Machines fast and reliable, allowing our research teams to focus on science, not system bottlenecks.</p>\n<p>Key responsibilities include designing, implementing, and optimizing distributed training systems, developing high-performance optimizations, and establishing standards for reliability, maintainability, and security. You&#39;ll collaborate with researchers and engineers to build scalable infrastructure and publish learnings through internal documentation, open-source libraries, or technical reports.</p>\n<p>We&#39;re looking for someone who blends deep systems and performance expertise with a curiosity for machine learning at scale. A strong understanding of deep learning frameworks, such as PyTorch, and experience working on distributed training for large models are preferred. 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We sponsor visas and offer generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b79d9627-55a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Thinking Machines Lab","sameAs":"https://thinkingmachines.ai/","logo":"https://logos.yubhub.co/thinkingmachines.ai.png"},"x-apply-url":"https://job-boards.greenhouse.io/thinkingmachines/jobs/5013932008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000 - $475,000 USD per year","x-skills-required":["deep learning frameworks","distributed training","high-performance optimizations","reliability, maintainability, and security","scalable infrastructure"],"x-skills-preferred":["past experience working on distributed training for large models","track record of improving research productivity through infrastructure design or process improvements","contributions to open-source ML infrastructure"],"datePosted":"2026-04-18T15:57:59.640Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"deep learning frameworks, distributed training, high-performance optimizations, reliability, maintainability, and security, scalable infrastructure, past experience working on distributed training for large models, track record of improving research productivity through infrastructure design or process improvements, contributions to open-source ML infrastructure","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":475000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_07a3c83e-51e"},"title":"Research Engineer, Infrastructure, Numerics","description":"<p>We&#39;re looking for an infrastructure research engineer to design and build the core systems that enable efficient large-scale model training with a focus on numerics. You will focus on improving the numerical foundations of our distributed training stack, from precision formats and kernel optimizations to communication frameworks that make training trillion-parameter models stable, scalable, and fast.</p>\n<p>This role is ideal for someone who thrives at the intersection of research and systems engineering: a builder who understands both the math of optimization and the realities of distributed compute.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design and optimize distributed training infrastructure for large-scale LLMs, focusing on performance, stability, and reproducibility across multi-GPU and multi-node setups.</li>\n<li>Implement and evaluate low-precision numerics (for example, BF16, MXFP8, NVFP4) to improve efficiency without sacrificing model quality.</li>\n<li>Develop kernels and communication primitives that use hardware-level support for mixed and low-precision arithmetic.</li>\n<li>Collaborate with research teams to co-design model architectures and training recipes that align with emerging numeric formats and stability constraints.</li>\n<li>Prototype and benchmark scaling strategies such as data, tensor, and pipeline parallelism that integrate precision-adaptive computation and quantized communication.</li>\n<li>Contribute to the design of our internal orchestration and monitoring systems to ensure that thousands of distributed experiments can run efficiently and reproducibly.</li>\n<li>Publish and share learnings through internal documentation, open-source libraries, or technical reports that advance the field of scalable AI infrastructure.</li>\n</ul>\n<p>Skills and Qualifications:</p>\n<p>Minimum qualifications:</p>\n<ul>\n<li>Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar.</li>\n<li>Understanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures.</li>\n<li>Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.</li>\n<li>A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.</li>\n<li>Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases in areas such as floating-point numerics, low-precision arithmetic, and distributed systems.</li>\n</ul>\n<p>Preferred qualifications , we encourage you to apply if you meet some but not all of these:</p>\n<ul>\n<li>Familiarity with distributed frameworks such as PyTorch/XLA, DeepSpeed, Megatron-LM.</li>\n<li>Experience implementing FP8, INT8, or block-floating point (MX) formats and understanding their numerical trade-offs.</li>\n<li>Prior contributions to open-source deep learning infrastructure such as PyTorch, DeepSpeed, or XLA.</li>\n<li>Publications, patents, or projects related to numerical optimization, communication-efficient training, or systems for large models.</li>\n<li>Experience training and supporting large-scale AI models.</li>\n<li>Track record of improving research productivity through infrastructure design or process improvements.</li>\n</ul>\n<p>Logistics:</p>\n<ul>\n<li>Location: This role is based in San Francisco, California.</li>\n<li>Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.</li>\n<li>Visa sponsorship: We sponsor visas. 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You will develop high-performance ML kernels (e.g., CUDA, CuTe, Triton), enable efficient low-precision arithmetic, and improve the distributed compute stack that makes training large models possible.</p>\n<p>This role is perfect for an engineer who enjoys working close to the metal and across the research boundary. You&#39;ll collaborate with researchers and systems architects to bridge algorithmic design with hardware efficiency. You&#39;ll prototype new kernel implementations, profile performance across hardware generations, and help define the numerical and parallelism strategies that determine how we scale next-generation AI systems.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design and implement custom ML kernels (e.g., CUDA, CuTe, Triton) for core LLM operations such as attention, matrix multiplication, gating, and normalization, optimized for modern GPU and accelerator architectures.</li>\n<li>Design and think through compute primitives to reduce memory bandwidth bottlenecks and improve kernel compute efficiency.</li>\n<li>Collaborate with research teams to align kernel-level optimizations with model architecture and algorithmic goals.</li>\n<li>Develop and maintain a library of reusable kernels and performance benchmarks that serve as the foundation for internal model training.</li>\n<li>Contribute to infrastructure stability and scalability, ensuring reproducibility, consistency across precision formats, and high utilization of compute resources.</li>\n<li>Document and share insights through internal talks, technical papers, or open-source contributions to strengthen the broader ML systems community.</li>\n</ul>\n<p><strong>Skills and Qualifications</strong></p>\n<p>Minimum qualifications:</p>\n<ul>\n<li>Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar.</li>\n<li>Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases</li>\n<li>Understanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures.</li>\n<li>Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.</li>\n<li>A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make 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Eager to learn and values continued self-development</li>\n</ul>\n<p>Why join us?</p>\n<ul>\n<li>Be a part of this values-driven, high-growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves.</li>\n<li>We’re a hybrid model with flexibility, allowing you to work how best suits you.</li>\n<li>25 days holiday (plus bank holidays) with an additional day to celebrate your birthday.</li>\n<li>Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey.</li>\n<li>Financial security and to work with you on our allocated dog-friendly days and spaces and not to forget our generous product discount and gifting!</li>\n</ul>\n<p>At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves. We celebrate and support this by encouraging and hiring people with diverse backgrounds, cultures, voices, beliefs, and perspectives into our growing global workforce. By doing so, we better serve our communities, customers, employees - and the candidates that take part in our recruitment process.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f58554b8-c3f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Charlotte Tilbury Beauty","sameAs":"https://www.charlottetilbury.com/","logo":"https://logos.yubhub.co/charlottetilbury.com.png"},"x-apply-url":"https://apply.workable.com/j/A1EAD29462","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["digital project management","translations or localisation project management","workflow platforms","process improvements","automation or AI-enabled workflows","budget management","cross-functional dependencies","team leadership","project management systems"],"x-skills-preferred":[],"datePosted":"2026-03-20T16:14:02.349Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London"}},"employmentType":"FULL_TIME","occupationalCategory":"Marketing","industry":"Beauty","skills":"digital project management, translations or localisation project management, workflow platforms, process improvements, automation or AI-enabled workflows, budget management, cross-functional dependencies, team leadership, project management systems"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_af9fbdd4-2b6"},"title":"Model Risk Management Governance, Associate","description":"<p><strong>About this role</strong></p>\n<p>The mission of the Risk and Quantitative Analysis (RQA) function is to help BlackRock manage its fiduciary and enterprise risks and provide independent oversight. 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Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. 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You&#39;ll leverage your consultative sales expertise in the Insurance sector to propel revenue growth while becoming a trusted partner to Enterprise stakeholders, helping them embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM, Product, and Marketing teams, you&#39;ll continuously refine our value proposition, sales methodology, and market positioning to resonate with Insurance decision-makers.</p>\n<p>Responsibilities:</p>\n<ul>\n<li><p>Win new business and drive revenue for Anthropic within the Insurance sector. Navigate complex institutions to reach key decision-makers, educate them about our services, and help them succeed with Anthropic. You&#39;ll own the full sales cycle, from first outbound to close</p>\n</li>\n<li><p>Design and execute innovative sales strategies tailored to Insurance procurement cycles and budgeting processes to meet and exceed revenue quotas. 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Identify process improvements that optimize sales productivity and consistency</p>\n</li>\n</ul>\n<p>You may be a good fit if you have:</p>\n<ul>\n<li><p>5+ years of B2B sales experience in Insurance technology, preferably in SaaS or emerging technologies</p>\n</li>\n<li><p>A track record of managing complex sales cycles within Insurance organizations and securing strategic deals by understanding both technical requirements and use cases</p>\n</li>\n<li><p>Demonstrated ability to navigate Insurance bureaucracies and procurement processes, building consensus among diverse stakeholders including executives, administrators, and IT departments</p>\n</li>\n<li><p>Extensive experience negotiating complex agreements within Insurance procurement frameworks and policies</p>\n</li>\n<li><p>Proven experience exceeding revenue targets in the Insurance sector by effectively managing an evolving pipeline and sales process</p>\n</li>\n<li><p>Excellent communication skills and the ability to present confidently to various audiences within Insurance</p>\n</li>\n<li><p>Deep understanding of Insurance buying cycles, decision-making processes, and key pain points</p>\n</li>\n<li><p>A strategic, analytical approach to assessing the Insurance market combined with creative, tactical execution to capture opportunities</p>\n</li>\n<li><p>A passion for and/or experience with advanced AI systems and their applications in Insurance. 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In this role, you will recruit and develop a team of world-class sellers, drive excellence across PG and MEDDPICC, and define how we land and grow within the world&#39;s largest and most complex organisations.</p>\n<p><strong>What you&#39;ll be doing...</strong></p>\n<ul>\n<li>Lead our EMEA-based UK/I Accounts team to drive predictable Annual Recurring Revenue (ARR) by landing and expanding Synthesia&#39;s highest-value customers (10k+ employees).</li>\n</ul>\n<ul>\n<li>Own pipeline quality and rigour, ensuring the team builds a robust, data-backed pipeline that creates confidence in future revenue and supports accurate forecasting.</li>\n</ul>\n<ul>\n<li>Refine and execute a comprehensive account strategy, leveraging your experience to deepen relationships within key accounts, elevate our reach to the executive level, and accelerate expansion motions.</li>\n</ul>\n<ul>\n<li>Partner with Talent Acquisition to hire and develop a world-class team, ensuring we attract top-tier, MEDDPICC-savvy sellers.</li>\n</ul>\n<ul>\n<li>Shape a high-performance culture where senior sellers are coached, empowered, and given a clear path to thrive and grow at Synthesia.</li>\n</ul>\n<ul>\n<li>Champion a Pipeline Generation (PG) mindset, reinforcing that outbound is a shared responsibility and a core competitive advantage.</li>\n</ul>\n<ul>\n<li>Work cross-functionally with Marketing and Customer Success to drive seamless alignment across the commercial organisation, maximising customer satisfaction, engagement, and long-term value.</li>\n</ul>\n<ul>\n<li>Continuously enhance our sales playbooks, embedding best practices, process improvements, and MEDDPICC methodologies that elevate the consistency and effectiveness of the entire sales function.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>You&#39;re a true first-line leader at heart - motivated, hands-on, and passionate about coaching teams to success every day.</li>\n</ul>\n<ul>\n<li>You&#39;ve recruited senior sellers who have thrived (recruiting is the number 1 priority of every GTM leader at Synthesia).</li>\n</ul>\n<ul>\n<li>Proven track record managing senior sellers carrying $1M+ quotas, who consistently win and grow large, complex organisations (10k+ employees).</li>\n</ul>\n<ul>\n<li>You&#39;ve sold across lines of business, not just IT. 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You can find out more about these principles here.</p>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>A hybrid setting where you can work from our London office.</li>\n</ul>\n<ul>\n<li>Paid parental leave entitles primary caregivers to 16 weeks of full pay, and secondary 5 weeks of full pay.</li>\n</ul>\n<ul>\n<li>25 days of annual leave + public holidays.</li>\n</ul>\n<ul>\n<li>Cycle to work scheme (London).</li>\n</ul>\n<ul>\n<li>Private Medical Insurance (Medical History Disregarded basis), including mental health support, dental &amp; vision, cashback and gym discounts.</li>\n</ul>\n<ul>\n<li>A generous referral scheme if you help us hire.</li>\n</ul>\n<ul>\n<li>Pension contribution/salary sacrifice.</li>\n</ul>\n<ul>\n<li>Work from home set up.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_a4b815b6-8a0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Synthesia","sameAs":"https://www.synthesia.io/","logo":"https://logos.yubhub.co/synthesia.io.png"},"x-apply-url":"https://jobs.ashbyhq.com/synthesia/7221d32e-c95f-48b3-b60c-cc07fb177c9c","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$200 million Series E funding round, with a valuation of $4 billion","x-skills-required":["value-driven sales","methodological sales","playbook sales","MEDDPICC","Command of the Message","executive presence","outstanding communication skills"],"x-skills-preferred":["pipeline generation","pipeline quality and rigour","account strategy","talent acquisition","sales playbooks","process improvements","cross-functional collaboration"],"datePosted":"2026-03-06T18:41:24.824Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London"}},"employmentType":"FULL_TIME","occupationalCategory":"Sales","industry":"Technology","skills":"value-driven sales, methodological sales, playbook sales, MEDDPICC, Command of the Message, executive presence, outstanding communication skills, pipeline generation, pipeline quality and rigour, account strategy, talent acquisition, sales playbooks, process improvements, cross-functional collaboration"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d52d568d-49b"},"title":"Forward Deployed Engineer (FDE), Life Sciences","description":"<p><strong>Forward Deployed Engineer (FDE), Life Sciences - NYC</strong></p>\n<p><strong>Location</strong></p>\n<p>New York City</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Location Type</strong></p>\n<p>Hybrid</p>\n<p><strong>Department</strong></p>\n<p>Model Deployment for Business</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$198K – $335K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. 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We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.</p>\n<p><strong>About the role</strong></p>\n<p>We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.</p>\n<p>You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.</p>\n<p>This role is based in NYC. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.</p>\n<p><strong>In this role you will</strong></p>\n<ul>\n<li>Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.</li>\n</ul>\n<ul>\n<li>Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.</li>\n</ul>\n<ul>\n<li>Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.</li>\n</ul>\n<ul>\n<li>Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.</li>\n</ul>\n<ul>\n<li>Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.</li>\n</ul>\n<ul>\n<li>Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.</li>\n</ul>\n<p><strong>You might thrive in this role if you</strong></p>\n<ul>\n<li>Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.</li>\n</ul>\n<ul>\n<li>Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.</li>\n</ul>\n<ul>\n<li>Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.</li>\n</ul>\n<ul>\n<li>Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.</li>\n</ul>\n<ul>\n<li>Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and process improvements.</li>\n</ul>\n<p><strong>What we offer</strong></p>\n<ul>\n<li>Competitive salary and equity package</li>\n</ul>\n<ul>\n<li>Opportunity to work with a talented team of engineers and researchers</li>\n</ul>\n<ul>\n<li>Collaborative and dynamic work environment</li>\n</ul>\n<ul>\n<li>Professional development and growth opportunities</li>\n</ul>\n<ul>\n<li>Flexible work arrangements</li>\n</ul>\n<ul>\n<li>Comprehensive benefits package</li>\n</ul>\n<ul>\n<li>Access to cutting-edge technology and resources</li>\n</ul>\n<p><strong>How to apply</strong></p>\n<p>If you are a motivated and talented individual who is passionate about AI and life sciences, we encourage you to apply for this exciting opportunity. Please submit your resume and a cover letter explaining why you are a strong fit for this role.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d52d568d-49b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/55e611d8-b284-458e-908c-baccd091d0c0","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$198K – $335K","x-skills-required":["software/ML engineering","technical deployment","customer-facing ownership","biotech","pharma","clinical research","scientific software","PhD","MS","equivalent applied experience","life sciences relevant field","GenAI deployments","evaluation design","error analysis","iterative evidence generation","validation strategy","auditability","compliance constraints","reviewer expectations","system design and rollout","scientific operations","trial design","regulatory writing","scientific operations","validation artifacts","process improvements"],"x-skills-preferred":["AI","life sciences","software development","data analysis","machine learning","deep learning","natural language processing","computer vision","robotics","autonomous systems"],"datePosted":"2026-03-06T18:41:01.225Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software/ML engineering, technical deployment, customer-facing ownership, biotech, pharma, clinical research, scientific software, PhD, MS, equivalent applied experience, life sciences relevant field, GenAI deployments, evaluation design, error analysis, iterative evidence generation, validation strategy, auditability, compliance constraints, reviewer expectations, system design and rollout, scientific operations, trial design, regulatory writing, scientific operations, validation artifacts, process improvements, AI, life sciences, software development, data analysis, machine learning, deep learning, natural language processing, computer vision, robotics, autonomous systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":198000,"maxValue":335000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5dec5a95-180"},"title":"Global Candidate Experience Manager","description":"<p><strong>Global Candidate Experience Manager</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>People</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$266K – $295K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. 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Your expertise and innovative approach will enable us to deliver high-quality solutions that meet the evolving needs of our clients.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_48fa8aff-aee","directApply":true,"hiringOrganization":{"@type":"Organization","name":"MHP - A Porsche Company","sameAs":"https://www.mhp.com","logo":"https://logos.yubhub.co/mhp.com.png"},"x-apply-url":"https://jobs.porsche.com/index.php?ac=jobad&id=19080","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"Salary range not stated","x-skills-required":["SAP SD","O2C processes","automotive processes","analytical skills","communication skills"],"x-skills-preferred":["innovative solutions","process improvements","cross-functional collaboration"],"datePosted":"2025-12-24T10:04:39.749Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Deutschlandweit & Hybrid Work"}},"employmentType":"FULL_TIME","occupationalCategory":"Consulting","industry":"Technology","skills":"SAP SD, O2C processes, automotive processes, analytical skills, communication skills, innovative solutions, process improvements, cross-functional collaboration"}]}