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Contribute to building models that can see, hear, reason about, and interact with the world in real time at unprecedented levels.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design, build, and optimize large-scale distributed systems for multimodal pre-training, post-training, inference, data processing, and tokenization at web/petabyte scale.</li>\n<li>Develop high-throughput pipelines for data acquisition, preprocessing, filtering, generation, decoding, loading, crawling, visualization, and management (images, videos, audio + text).</li>\n<li>Advance multimodal capabilities including spatial-temporal compression, cross-modal alignment, world modeling, reasoning, emergent abilities, audio/image/video understanding &amp; generation, real-time video processing, and noisy data handling.</li>\n<li>Drive data quality and studies: curation (human/synthetic), filtering techniques, analysis, and scalable pipelines to support trillion-parameter models.</li>\n<li>Create evaluation frameworks, internal benchmarks, reward models, and metrics that capture real-world usage, failure modes, interactive dynamics, and human-AI synergy.</li>\n<li>Innovate on algorithms, modeling approaches, hardware/software/algorithm co-design, and scaling paradigms for state-of-the-art performance.</li>\n<li>Build research tooling, user-friendly interfaces, prototypes/demos, full-stack applications, and enable rapid iteration based on feedback.</li>\n<li>Work across the stack (pre-training → SFT/RL/post-training) to enable reasoning, tool calling, agentic behaviors, orchestration, and seamless real-time interactions.</li>\n</ul>\n<p><strong>Basic Qualifications</strong></p>\n<ul>\n<li>Hands-on experience with multimodal pre-training, post-training, or fine-tuning (vision, audio, video, or cross-modal).</li>\n<li>Expert-level proficiency in Python (core language), with strong experience in at least one of: JAX / PyTorch / XLA.</li>\n<li>Proven track record building or optimizing large-scale distributed ML systems (training/inference optimization, GPU utilization, multi-GPU/TPU setups, hardware co-design).</li>\n<li>Deep experience designing and running data pipelines at scale: curation, filtering, generation, quality studies, especially for noisy/real-world multimodal data.</li>\n<li>Strong fundamentals in evaluation design, benchmarks, reward modeling, or RL techniques (particularly for interactive/agentic behaviors).</li>\n<li>Proactive self-starter who thrives in high-intensity environments and is passionate about pushing multimodal AI frontiers.</li>\n<li>Willingness to own end-to-end initiatives and do whatever it takes to deliver breakthrough user experiences.</li>\n</ul>\n<p><strong>Preferred Skills and Experience</strong></p>\n<ul>\n<li>Experience leading major improvements in model capabilities through better data, modeling, algorithms, or scaling.</li>\n<li>Familiarity with state-of-the-art in multimodal LLMs, scaling laws, tokenizers, compression techniques, reasoning, or agentic systems.</li>\n<li>Proficiency in Rust and/or C++ for performance-critical components.</li>\n<li>Hands-on work with large-scale orchestration tools such as Spark, Ray, or Kubernetes.</li>\n<li>Background building full-stack tooling: performant interfaces, real-time research demos/apps, or end-to-end product ownership.</li>\n<li>Passion for end-to-end user experience in interactive, real-time multimodal AI systems.</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_540ce49c-271","directApply":true,"hiringOrganization":{"@type":"Organization","name":"xAI","sameAs":"https://www.xai.com","logo":"https://logos.yubhub.co/xai.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/xai/jobs/5111374007","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$180,000 - 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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. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p><strong>About the team</strong></p>\n<p>OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&amp;D value chain to help customers design and ship production-grade AI systems. 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_b4b28851-8f4"},"title":"Forward Deployed Engineer (FDE), Life Sciences - SF","description":"<p><strong>Forward Deployed Engineer (FDE), Life Sciences - SF</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>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. 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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 Paris. 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 repeatable deployment playbooks.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. 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