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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b7795adf-116"},"title":"Spatial Transcriptomic Postdoc Scientist","description":"<p>As a Postdoctoral Scientist, you will serve as a key technical transcriptomics expert within Plant Biotechnology at Bayer Crop Science R&amp;D.</p>\n<p>You will be responsible for the execution and analysis of single-cell or spatial transcriptomics and technical reporting.</p>\n<p>With a focus on functional genomics, you will provide insights to support decision-making, problem-solving, and pipeline innovation.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Analyze spatial transcriptomic data for quality assessment and evaluation of experimental success;</li>\n<li>Conduct in-depth data analyses and design controlled experiments in collaboration with cross-functional partners, coordinating their implementation to enable project success;</li>\n<li>Establish and optimize RNA sequencing protocols for single-cell or spatial transcriptomics applications;</li>\n<li>Understand and anticipate broader project/team interests, identifying, proposing, and performing complementary analyses to enrich insights from multiple modalities/data layers;</li>\n<li>Demonstrate commitment to inclusion and safety, adhering to safety protocols and best practices;</li>\n<li>Maintain detailed record-keeping and required documentation;</li>\n<li>Thrive on meeting challenges, insisting on high-quality deliverables, and demonstrating effective problem-solving skills while building productive external and internal relationships;</li>\n<li>Conduct complex activities that require specialized knowledge and the broad application of scientific principles;</li>\n<li>Take initiative in keeping current with literature in areas of assignment and professional interest.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Ph.D. in a biological/biomedical, molecular or cell biology, genetics/genomics, computational field, or similar area;</li>\n<li>Experience with next-generation sequencing library preparation;</li>\n<li>Experience with next-generation transcriptomics analysis or a related area;</li>\n<li>Familiarity with innovative or emerging fields of study.</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Familiarity with spatial transcriptomics methodologies for analysis;</li>\n<li>Experience working in a Linux environment and at least one programming language (Python, R, etc.);</li>\n<li>Library preparation for cell-based resolution transcriptomics techniques (such as single-cell RNA sequencing or spatial transcriptomics libraries);</li>\n<li>Experience with agricultural specimens;</li>\n<li>Experience collaborating across multiple teams, fostering a team-based approach to research, and leveraging partnerships;</li>\n<li>Experience clearly communicating project plans and experimental results with partners and stakeholders, maintaining alignment on objectives and priorities.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<p>Employees can expect to be paid a salary between $78,640.00 - $117,960.00. Additional compensation may include a bonus or incentive compensation. 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This is an exciting opportunity for a talented and passionate individual to join a multidisciplinary team of vegetable breeders, horticultural scientists, data scientists, and engineers.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Plan and execute experimental protocols and performance trials in protected culture and open field environments.</li>\n<li>Operate research equipment, take notes, enter data management with internal IT systems, and comply with seed stewardship standards.</li>\n<li>Develop, execute, and continuously improve strategic testing plans in alignment with business objectives to deliver results within the crops.</li>\n<li>Execute protocols and trials to generate quality data enabling breeding partners to advance new products based on performance and market needs.</li>\n<li>Capture data in Windows and iOS operating systems and conduct data quality checks and assurance.</li>\n<li>Leverage metrics applications and quality control processes to realize accuracy, efficiency, and expanded improvements to protocols.</li>\n<li>Manage relationships with growers and third-party cooperators to ensure timely completion and integrity of data collected.</li>\n<li>Create and use tools from collected and analyzed data to develop the performance story and support the transfer of product and agronomic knowledge.</li>\n<li>Explore new technologies to increase capacity, speed up current processes, and deploy novel technologies in data collection and crop management.</li>\n<li>Perform tasks to ensure compliance with Bayer policies and quality standards.</li>\n<li>Work extended hours during peak seasons, including non-traditional day-time hours with potential overnight travel.</li>\n</ul>\n<p><strong>Requirements:</strong></p>\n<ul>\n<li>BSc. in Horticulture, Agronomy, or a related field with a minimum of 5 years of crop management experience.</li>\n<li>Knowledge and experience with agricultural equipment and vegetable crops production practices.</li>\n<li>History of leveraging technology for crop management and data collection.</li>\n</ul>\n<p><strong>Preferred Qualifications:</strong></p>\n<ul>\n<li>PhD with 1 year of experience or MSc with 3 years of experience in related fields.</li>\n</ul>\n<p><strong>Compensation:</strong></p>\n<ul>\n<li>Salary between $78,640.00 - $117,960.00</li>\n<li>Additional compensation may include a bonus or incentive compensation</li>\n<li>Benefits include health care, vision, dental, retirement, PTO, sick leave, etc.</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_c2c02776-eeb","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Bayer","sameAs":"https://talent.bayer.com","logo":"https://logos.yubhub.co/talent.bayer.com.png"},"x-apply-url":"https://talent.bayer.com/careers/job/562949978264379?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$78,640.00 - $117,960.00","x-skills-required":["Horticulture","Agronomy","Crop Management","Data Collection","Technology"],"x-skills-preferred":["PhD","MSc"],"datePosted":"2026-07-27T18:09:45.666Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Payette, Idaho"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Agriculture","skills":"Horticulture, Agronomy, Crop Management, Data Collection, Technology, PhD, MSc","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":78640,"maxValue":117960,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_a85447d7-164"},"title":"Research Scientist I/II","description":"<p>At Freenome, you will help develop assay technologies used to analyze patient samples and contribute to the mission of early detection and intervention in human disease.</p>\n<p>As a Research Scientist I/II, you will provide experience in next-generation-sequencing (NGS)-based analyses of DNA. You will contribute to the program&#39;s technical base by creating and optimizing new next-generation sequencing (NGS) assays and workflows for DNA/RNA, or to the program&#39;s scientific base by elevating the understanding of the biological context of these assay signals in cancer.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Independently design and execute experiments to help optimize the performance of Freenome&#39;s new or existing assays.</li>\n<li>Prototype new next-generation sequencing (NGS) methods, optimize the performance of existing assays, and execute biomarker discovery studies on clinical samples.</li>\n<li>Assist with project planning and timeline generation and work with cross-functional teams to coordinate tasks within and across projects.</li>\n<li>Take detailed notes, gather high-quality data, and openly communicate on lessons learned while performing experiments.</li>\n<li>Independently troubleshoot workflows and understand the rationale behind workflow optimization choices.</li>\n<li>Help with process improvements across the lab by thinking critically about the execution of all experiments.</li>\n<li>Perform advanced analysis and data visualization of results to answer experimental questions and guide next steps.</li>\n<li>Prepare and present experiment or project results at internal meetings, with clear articulation of goals, results, conclusions, and how results presented fit into broader project.</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>PhD in molecular biology, biochemistry, genetics, or a related field or Bachelor&#39;s or Master&#39;s with 8+ years experience post-Bachelor&#39;s in the life sciences (industry and/or academia).</li>\n<li>Hands-on experience with and expert-level knowledge in NGS-based workflows including sample preparation, library preparation, target capture, and sequencing.</li>\n<li>Biological understanding of human cell-free nucleic acids, single-cell analysis methods, immunology, and/or cancer biology.</li>\n<li>Ability to perform advanced data analysis and critically examine experimental results.</li>\n<li>Proven track record of designing and running successful experiments, preparing data for review, and giving effective scientific presentations.</li>\n<li>Clear and proactive communication skills and ability to collaborate effectively with team members in the same and adjacent disciplines.</li>\n<li>Flexible and highly motivated to learn new skills and comfortable adapting to changing priorities.</li>\n</ul>\n<p>Nice to haves:</p>\n<ul>\n<li>Ability to perform bioinformatic analysis in a scientific programming language (e.g., Python or R).</li>\n<li>Experience handling and preparing blood and/or tissue samples.</li>\n<li>Experience running high-throughput experimental designs and/or assays on an automated liquid handling platform.</li>\n<li>Experience using ELN (electronic lab notebook) and LIMS (lab information management system).</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>The US target range of our base salary rate for new hires is $132,050 - 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Starting with a prototype assay, you will contribute to developing and validating clinical-grade assays to measure complex, blood-based analytes.</p>\n<p>You will work closely with multiple teams including molecular research, computational science, automation engineering, and clinical operations to develop assays in a regulated, high-throughput environment. You will also identify ways to rapidly iterate and improve on existing methods to evaluate technologies that can enhance end-to-end test performance.</p>\n<p>The role reports to the Senior Manager and Staff Research Scientist. This role will be an onsite role.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Apply knowledge of molecular biology, nucleic-acid biochemistry, and next-generation sequencing to develop assays for DNA.</li>\n<li>Characterise automated assays by generating and analysing experimental data.</li>\n<li>Gather high-quality data, take detailed notes, and openly communicate on lessons learned while performing experiments.</li>\n<li>Collaborate with research teams and computational biologists, understand how data reflect underlying molecular biology, and contribute to analysing data and generating study conclusions.</li>\n<li>Present data in cross-functional teams.</li>\n<li>Participate in troubleshooting efforts and design experiments with some supervisor guidance.</li>\n<li>Help with process improvements across the lab by thinking critically about the execution of all experiments.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Bachelor&#39;s degree with 1+ years of relevant industry experience or Master&#39;s degree in molecular biology, or a related field.</li>\n<li>Hands-on experience in NGS-based assay development including sample preparation, library preparation, target capture, and sequencing.</li>\n<li>Biological understanding of human cell-free nucleic acids, single-cell analysis methods, immunology, and/or cancer biology.</li>\n<li>High attention to detail and ability to record accurate and detailed observations, assess impact, and perform troubleshooting as required.</li>\n<li>Flexible and highly motivated to learn new skills and comfortable adapting to changing priorities.</li>\n<li>Ability to manually pipette with high confidence, accuracy, and precision.</li>\n<li>Clear and proactive communication skills and ability to collaborate effectively with team members in the same and adjacent disciplines.</li>\n</ul>\n<p><strong>Nice to Have</strong></p>\n<ul>\n<li>Experience working in a regulated laboratory environment (CLIA, GLP/GCLP, IVD development).</li>\n<li>Experience with automated platforms in plate-based, low-volume formats and/or microfluidics and experience working with automated liquid handlers.</li>\n<li>Experience using ELN (electronic lab notebook) and LIMS (lab information management system).</li>\n<li>Familiarity with programming in a scientific programming language (e.g., Python or R).</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>The US target range of our base hourly rate for new hires is $37.68 - $46.69.</li>\n<li>You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.</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_a368ee95-84f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Freenome","sameAs":"https://www.freenome.com/job-openings/","logo":"https://logos.yubhub.co/freenome.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/freenome/jobs/8637437002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"onsite","x-experience-level":"entry","x-job-type":"full-time","x-salary-range":"$37.68 - $46.69","x-skills-required":["molecular biology","nucleic-acid biochemistry","next-generation sequencing","NGS-based assay development","sample preparation","library preparation","target capture","sequencing"],"x-skills-preferred":["regulated laboratory environment","automated platforms","plate-based formats","microfluidics","automated liquid handlers","ELN","LIMS","Python","R"],"datePosted":"2026-07-24T18:13:58.241Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Brisbane, California"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Healthcare","skills":"molecular biology, nucleic-acid biochemistry, next-generation sequencing, NGS-based assay development, sample preparation, library preparation, target capture, sequencing, regulated laboratory environment, automated platforms, plate-based formats, microfluidics, automated liquid handlers, ELN, LIMS, Python, R"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ce374ba5-d77"},"title":"Research Associate I/II","description":"<p>At Freenome, you will help develop assay technologies used to analyze patient samples and contribute to the mission of early detection and intervention in human disease.</p>\n<p>As a Research Associate I/II, you will provide experience in next-generation-sequencing (NGS)-based analyses of DNA. Starting with a prototype assay, you will contribute to developing and validating clinical-grade assays to measure complex, blood-based analytes.</p>\n<p>You will work closely with multiple teams including molecular research, computational science, automation engineering, and clinical operations to develop assays in a regulated, high-throughput environment. You will also identify ways to rapidly iterate and improve on existing methods to evaluate technologies that can enhance end-to-end test performance.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Apply knowledge of molecular biology, nucleic-acid biochemistry, and next-generation sequencing to develop assays for DNA.</li>\n<li>Characterize automated assays by generating and analyzing experimental data.</li>\n<li>Gather high-quality data, take detailed notes, and openly communicate on lessons learned while performing experiments.</li>\n<li>Collaborate with research teams and computational biologists, understand how data reflect underlying molecular biology, and contribute to analyzing data and generating study conclusions.</li>\n<li>Present data in cross-functional teams.</li>\n<li>Participate in troubleshooting efforts and design experiments with some supervisor guidance.</li>\n<li>Help with process improvements across the lab by thinking critically about the execution of all experiments.</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>Bachelor&#39;s degree with 1+ years of relevant industry experience or Master&#39;s degree in molecular biology, or a related field.</li>\n<li>Hands-on experience in NGS-based assay development including sample preparation, library preparation, target capture, and sequencing.</li>\n<li>Biological understanding of human cell-free nucleic acids, single-cell analysis methods, immunology, and/or cancer biology.</li>\n<li>High attention to detail and ability to record accurate and detailed observations, assess impact, and perform troubleshooting as required.</li>\n<li>Flexible and highly motivated to learn new skills and comfortable adapting to changing priorities.</li>\n<li>Ability to manually pipette with high confidence, accuracy, and precision.</li>\n<li>Clear and proactive communication skills and ability to collaborate effectively with team members in the same and adjacent disciplines.</li>\n</ul>\n<p>Nice to haves:</p>\n<ul>\n<li>Experience working in a regulated laboratory environment (CLIA, GLP/GCLP, IVD development).</li>\n<li>Experience with automated platforms in plate-based, low-volume formats and/or microfluidics and experience working with automated liquid handlers.</li>\n<li>Experience using ELN (electronic lab notebook) and LIMS (lab information management system).</li>\n<li>Familiarity with programming in a scientific programming language (e.g., Python or R).</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>The US target range of our base hourly rate for new hires is $37.68 - $46.69.</li>\n<li>You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.</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_ce374ba5-d77","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Freenome","sameAs":"https://www.freenome.com/job-openings/","logo":"https://logos.yubhub.co/freenome.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/freenome/jobs/8637397002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"onsite","x-experience-level":"entry","x-job-type":"full-time","x-salary-range":"$37.68 - $46.69","x-skills-required":["molecular biology","nucleic-acid biochemistry","next-generation sequencing","NGS-based assay development","sample preparation","library preparation","target capture","sequencing"],"x-skills-preferred":["regulated laboratory environment","automated platforms","plate-based formats","microfluidics","automated liquid handlers","ELN","LIMS","Python","R"],"datePosted":"2026-07-24T18:13:39.388Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Brisbane, California"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Healthcare","skills":"molecular biology, nucleic-acid biochemistry, next-generation sequencing, NGS-based assay development, sample preparation, library preparation, target capture, sequencing, regulated laboratory environment, automated platforms, plate-based formats, microfluidics, automated liquid handlers, ELN, LIMS, Python, R"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_46528ba1-50e"},"title":"Research Program Manager, Human Data Campaigns","description":"<p><strong>Compensation</strong></p>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this role is $239K – $328K, with generous equity, performance-related bonuses, and the following benefits:</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n<li>401(k) retirement plan with employer match</li>\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<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\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<li>Mental health and wellness support</li>\n<li>Employer-paid basic life and disability coverage</li>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n<li>Relocation support for eligible employees</li>\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&#39;s Human Data Team creates custom data solutions driving groundbreaking research. Our work enhances and evaluates our flagship models and products like ChatGPT, GPT-5, and Sora, and contributes to safety initiatives through collaboration with our Preparedness and Safety Systems teams.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Research Program Manager (RPM) in the Human Data team, you will partner with research and engineering to design and implement pragmatic solutions for collecting high-quality data. You will be a key interface between our research roadmap, external vendors, AI trainers, and the Human Data engineering team.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Collaborate with researchers to scope data collection needs, define success metrics, and establish quality measurement frameworks.</li>\n<li>Design and execute data collection campaigns, translating research needs into actionable plans and accelerating execution by leveraging existing tooling and iterating to reach the desired outcome.</li>\n<li>Unblock yourself by figuring out how to achieve at least partial success in the interim, with the technical acumen and drive to implement scrappy new solutions.</li>\n<li>Optimize systems and processes by building and optimizing dashboards to track campaign performance, leveraging SQL and Python for data analysis and actionable insights.</li>\n<li>Drive technical roadmaps by collaborating with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management.</li>\n<li>Scale your impact by advising and empowering program managers and vendors to drive day-to-day execution, allowing you to focus on addressing high-priority opportunities.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Proficiency in SQL and Python for data analysis, including querying databases, processing large datasets, and generating actionable insights.</li>\n<li>Proficiency in Python for interacting with various tools via APIs, including sending requests, processing responses, and integrating functionalities into workflows.</li>\n<li>Proficiency in SQL for creating analytics dashboards, including writing complex queries, optimizing data retrieval, and visualizing insights for decision-making.</li>\n<li>Experience working at large scale across a portfolio of projects.</li>\n<li>Ability to get hands dirty, with grit and creative problem-solving required daily.</li>\n<li>Action-oriented and deeply curious mind.</li>\n<li>Ability to learn technical concepts exceptionally quickly, seeking out knowledge to become proficient in areas that are new to you.</li>\n<li>High horsepower, adept at frequent context switching and working on multiple projects at once with expansive ownership, and ruthless prioritization.</li>\n<li>Thrives in dynamic environments and can navigate ambiguity with ease.</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_46528ba1-50e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://www.openai.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/5edd5a13-2fc9-427c-ad88-2b67c97a0afe?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$239K - $328K","x-skills-required":["SQL","Python","data analysis","API integration","dashboard creation"],"x-skills-preferred":[],"datePosted":"2026-07-22T09:32:17.503Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Technology","skills":"SQL, Python, data analysis, API integration, dashboard creation","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":239000,"maxValue":328000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_801ae199-fc6"},"title":"Researcher, Alignment CoT Monitorability","description":"<p><strong>Compensation</strong></p>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this position is $250K – $445K, with generous equity, performance-related bonuses, and the following benefits:</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n<li>401(k) retirement plan with employer match</li>\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<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\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</li>\n<li>Mental health and wellness support</li>\n<li>Employer-paid basic life and disability coverage</li>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n<li>Relocation support for eligible employees</li>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends</li>\n</ul>\n<p><strong>About the Team</strong></p>\n<p>The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough to support scalable oversight. We focus on measuring monitorability, training mechanisms that affect monitorability, and methods to improve monitorability.</p>\n<p><strong>About the Role</strong></p>\n<p>We&#39;re looking for a researcher with strong empirical ML expertise and a deep interest in model behavior, alignment, or interpretability. As a researcher on the Alignment team, you will design and run experiments to improve our understanding of model monitorability, investigate how training interventions influence monitorability, and translate findings into practical oversight and training recommendations.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Design and run empirical studies of chain-of-thought monitorability across frontier reasoning models and training settings</li>\n<li>Build evaluations that measure whether monitors can reliably predict properties of interest, including high-stakes forms of misbehavior</li>\n<li>Investigate how pre-training, synthetic data, mid-training, post-training, reinforcement learning, and other interventions improve or degrade monitorability</li>\n<li>Analyze model behavior and turn observations from monitoring into hypotheses, experiments, and recommendations</li>\n<li>Translate research findings into practical monitoring and oversight approaches that can inform real training runs</li>\n<li>Collaborate with researchers and engineers across model training, alignment evaluations, monitoring, and frontier-risk work</li>\n<li>Produce externally publishable research when results advance the broader science of alignment</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have strong hands-on experience training, evaluating, or debugging large ML models, especially LLMs</li>\n<li>Have deep curiosity, interest in alignment, and high agency</li>\n<li>Bring depth in alignment, interpretability, model behavior, empirical ML, or adjacent research</li>\n<li>Are excited to investigate chain-of-thought monitorability, monitoring methods, and scalable oversight</li>\n<li>Can turn ambiguous research questions into measurable experiments and follow the evidence when results are subtle or noisy</li>\n<li>Move comfortably between research ideation and engineering execution</li>\n<li>Are curious about multiple approaches to understanding model behavior and are not committed to only one methodological lens</li>\n<li>Operate with high independence while collaborating closely across research and engineering teams</li>\n<li>Care about making increasingly capable AI systems more monitorable, trustworthy, and safe</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_801ae199-fc6","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://openai.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/82492010-ea96-449d-9949-b726b1a22616?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"hybrid","x-experience-level":null,"x-job-type":"Full time","x-salary-range":"$250K - $445K","x-skills-required":["empirical ML","model behavior","alignment","interpretability","LLMs"],"x-skills-preferred":["chain-of-thought interpretability","scalable oversight","monitoring methods"],"datePosted":"2026-06-29T19:13:03.763Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Technology","skills":"empirical ML, model behavior, alignment, interpretability, LLMs, chain-of-thought interpretability, scalable oversight, monitoring methods","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":250000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8eb98d0f-4bd"},"title":"Agent Post-Training, Personality","description":"<p><strong>Compensation</strong></p>\n<p>Estimated Base Salary $295K – $445K</p>\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<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n<li>401(k) retirement plan with employer match</li>\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<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\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<li>Mental health and wellness support</li>\n<li>Employer-paid basic life and disability coverage</li>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n<li>Relocation support for eligible employees</li>\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>The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve.</p>\n<p>We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste.</p>\n<p>Our team builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day.</p>\n<p><strong>About the Role</strong></p>\n<p>As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements.</p>\n<p>We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations.</p>\n<p>This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full training stack and reach the models people use every day.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Develop a rigorous understanding of what makes an agent a great collaborator across professional, creative, technical, and everyday work.</li>\n<li>Turn qualitative judgments about model behavior into concrete hypotheses, evals, graders, and training interventions.</li>\n<li>Study explicit and implicit user signals to understand which behaviors create trust, satisfaction, continued use, and successful outcomes.</li>\n<li>Work with human experts and trainers to produce high-quality, tasteful rollouts and preference data that capture excellent collaborative behavior.</li>\n<li>Improve reward models and RL objectives for model behaviors.</li>\n<li>Work with pretraining and early-training teams on data mixtures, objectives, synthetic data, and other upstream choices that shape downstream personality.</li>\n<li>Build sustainable pipelines for updating older training data as our understanding of excellent model behavior evolves.</li>\n<li>Partner closely with ChatGPT, Codex, and other product teams to turn consumer insight into model improvements and validate them in real workflows.</li>\n<li>Own projects end to end, from observing a subtle behavioral failure through experimentation, training, evaluation, and launch.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Think instinctively from the user’s perspective and care deeply about how models feel to work with, not only how they perform on benchmarks.</li>\n<li>Can translate subjective-seeming product questions into falsifiable hypotheses and rigorous evaluations without losing the nuance that made the question important.</li>\n<li>Care about preserving individuality, adaptability, and behavioral diversity rather than optimizing every model toward one narrow style.</li>\n<li>Want to shape how frontier agents communicate, collaborate, and build trust with millions of people.</li>\n<li>Have strong technical foundations in machine learning, software engineering, statistics, behavioral science, HCI, or a related field, and can quickly learn across unfamiliar parts of the stack.</li>\n<li>Have strong taste for model behavior: you can look at user feedback and can explain why one response feels thoughtful, natural, and useful while another does not.</li>\n<li>Have experience with LLMs, post-training, RL/RLHF, reward modeling, evals, synthetic data, pretraining data, or production ML systems.</li>\n<li>Are excited by ambiguous capability problems where the signal is noisy, the failures are qualitative, and the solution may involve data, training, evals, product changes, or all of the above.</li>\n<li>Can work effectively with researchers, engineers, product teams, designers, domain experts, human-data teams and safety boundaries, and can communicate clearly with each group.</li>\n<li>Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous.</li>\n<li>Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users.</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_8eb98d0f-4bd","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://www.openai.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/3302ceaf-f6ca-4803-9846-7fff7ad48a0d?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":null,"x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$295K - $445K","x-skills-required":["machine learning","software engineering","statistics","behavioral science","HCI"],"x-skills-preferred":["LLMs","post-training","RL/RLHF","reward modeling","evals","synthetic data","pretraining data","production ML systems"],"datePosted":"2026-06-27T18:19:23.349Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Artificial Intelligence","skills":"machine learning, software engineering, statistics, behavioral science, HCI, LLMs, post-training, RL/RLHF, reward modeling, evals, synthetic data, pretraining data, production ML systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":295000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5eb05828-829"},"title":"Agent Post-Training, Artifacts Research","description":"<p>We are seeking an Agent Post-Training, Artifacts Research to join our Research team in San Francisco.</p>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The estimated base salary for this role is $295K – $445K.</p>\n<p><strong>About the Team</strong></p>\n<p>The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve.</p>\n<p><strong>About the Role</strong></p>\n<p>As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design and run experiments that improve agentic model behavior for complex software and plugins.</li>\n<li>Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis.</li>\n<li>Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions.</li>\n<li>Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements.</li>\n<li>Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior.</li>\n<li>Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.</li>\n<li>Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.</li>\n<li>Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments.</li>\n<li>Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes.</li>\n</ul>\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<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit).</li>\n<li>401(k) retirement plan with employer match.</li>\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<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees.</li>\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.</li>\n<li>Mental health and wellness support.</li>\n<li>Employer-paid basic life and disability coverage.</li>\n<li>Annual learning and development stipend to fuel your professional growth.</li>\n<li>Daily meals in our offices, and meal delivery credits as eligible.</li>\n<li>Relocation support for eligible employees.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field.</li>\n<li>Hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.</li>\n<li>Experience with designing and running experiments, and analyzing results.</li>\n<li>Ability to work across research, product, infrastructure, data, evals, and safety boundaries.</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_5eb05828-829","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://openai.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/6897d024-88c1-43ed-adb8-5d2fc5eec984?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":null,"x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$295K - $445K","x-skills-required":["machine learning","software engineering","systems","statistics","LLMs","RL","RLHF/RLAIF","post-training","evals","graders","synthetic data","model training"],"x-skills-preferred":[],"datePosted":"2026-06-27T18:18:36.290Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Technology","skills":"machine learning, software engineering, systems, statistics, LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":295000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c80b1f21-eb4"},"title":"Agent Post-Training, Frontier Evals and Environments Research","description":"<p><strong>Compensation</strong></p>\n<p>Estimated Base Salary $295K – $445K</p>\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<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n<li>401(k) retirement plan with employer match</li>\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<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\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<li>Mental health and wellness support</li>\n<li>Employer-paid basic life and disability coverage</li>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n<li>Relocation support for eligible employees</li>\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>The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve.</p>\n<p>We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste.</p>\n<p>Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI&#39;s next agents can do, then carry those capabilities through major training runs and into the products people use.</p>\n<p><strong>About the Role</strong></p>\n<p>As a researcher working on Frontier Evals &amp; Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval, SWE-bench Verified, MLE-bench, PaperBench, and SWE-Lancer. If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you.</p>\n<p>You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models.</p>\n<p><strong>In this role, you might</strong></p>\n<ul>\n<li>Create ambitious RL environments to push our models to their limits, and measure frontier model capabilities, skills, and behaviors</li>\n<li>Develop new methodologies for automatically exploring the behavior of these models</li>\n<li>Dive deep into the science of measurement, including understanding scalability, reliability, and variance of our evaluation methodology</li>\n<li>Help steer training for our largest training runs, and see the future first</li>\n<li>Design scalable systems and processes to support continuous evaluation</li>\n<li>Build self-improvement loops to automate model understanding</li>\n</ul>\n<p><strong>You might thrive in this role if you</strong></p>\n<ul>\n<li>Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before.</li>\n<li>Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.</li>\n<li>Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution.</li>\n<li>Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with.</li>\n<li>Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next.</li>\n<li>Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group.</li>\n<li>Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous.</li>\n<li>Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users.</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_c80b1f21-eb4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://openai.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/9d72171e-2630-4347-83a1-263178644282?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":null,"x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$295K - $445K","x-skills-required":["machine learning","software engineering","systems","statistics","LLMs","RL","RLHF/RLAIF","post-training","evals","graders","synthetic data","model training","coding agents","tool-using agents","production ML systems"],"x-skills-preferred":[],"datePosted":"2026-06-27T18:18:02.258Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Artificial Intelligence","skills":"machine learning, software engineering, systems, statistics, LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, production ML systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":295000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c123699a-7bd"},"title":"Agent Post-Training, Context Research","description":"<p><strong>Job Overview</strong></p>\n<p>We are seeking an Agent Post-Training, Context Researcher to join our team at OpenAI. You will play a crucial role in scaling compute spent on context, working on the frontier training stack, and enabling the next paradigm of model training. This is a high-agency role for individuals who want their work to directly impact frontier models.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design and run experiments to improve the scaling of compute on context.</li>\n<li>Own end-to-end improvements to the post-training stack, including reinforcement learning, data pipelines, graders, reward signals, evaluations, diagnostics, and model-behavior analysis.</li>\n<li>Develop evaluations and environments that expose the next set of model failures and turn those failures into training data, product fixes, or new research directions.</li>\n<li>Collaborate with Codex and ChatGPT product teams to understand user needs and translate product signal into model improvements.</li>\n<li>Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and evaluation loops that shape downstream agent behavior.</li>\n<li>Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.</li>\n<li>Improve the machinery for large-scale training and launch, focusing on experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.</li>\n<li>Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field.</li>\n<li>Hands-on experience with large language models, reinforcement learning, post-training, evaluations, graders, synthetic data, model training, coding agents, tool-using agents, or production machine learning systems.</li>\n<li>Experience working across research, product, infrastructure, data, evaluations, and safety boundaries.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Estimated base salary: $295K - $445K</li>\n<li>Generous equity and performance-related bonuses</li>\n<li>Medical, dental, and vision insurance for you and your family</li>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses</li>\n<li>401(k) retirement plan with employer match</li>\n<li>Paid parental leave, medical and caregiver leave</li>\n<li>Flexible PTO and paid company holidays</li>\n<li>Mental health and wellness support</li>\n<li>Employer-paid basic life and disability coverage</li>\n<li>Annual learning and development stipend</li>\n<li>Daily meals in our offices and meal delivery credits</li>\n<li>Relocation support for eligible employees</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is committed to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of AI capabilities and seek to safely deploy them through our products.</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_c123699a-7bd","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://openai.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/df3edefb-6a8b-4ef6-b183-b3f96051783e?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":null,"x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$295K - $445K","x-skills-required":["machine learning","software engineering","systems","statistics","reinforcement learning","post-training","evaluations","graders","synthetic data","model training","coding agents","tool-using agents","production machine learning systems"],"x-skills-preferred":[],"datePosted":"2026-06-27T18:17:08.992Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Artificial Intelligence","skills":"machine learning, software engineering, systems, statistics, reinforcement learning, post-training, evaluations, graders, synthetic data, model training, coding agents, tool-using agents, production machine learning systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":295000,"maxValue":445000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e00aa734-e11"},"title":"Agent Post-Training, Connectors Research","description":"<p><strong>Compensation</strong></p>\n<p>Estimated Base Salary $295K – $445K</p>\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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You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use.</p>\n<p><strong>In this role, you might</strong></p>\n<ul>\n<li>Design and run experiments that improve agentic model behavior for complex software and plugins.</li>\n<li>Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis.</li>\n<li>Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions.</li>\n<li>Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements.</li>\n<li>Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior.</li>\n<li>Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.</li>\n<li>Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.</li>\n<li>Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments.</li>\n<li>Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes.</li>\n</ul>\n<p><strong>You might thrive in this role if you</strong></p>\n<ul>\n<li>Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before.</li>\n<li>Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.</li>\n<li>Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution.</li>\n<li>Care about product impact and model behavior, not just benchmark movement. 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is a reality.</p>\n<p>We&#39;re seeking a Director, In vivo Expert, CVRI (Cardiovascular, Renal &amp; Immunology) to join our Cardiorenal In Vivo Research group at the Bayer Innovation Campus in Cambridge, MA.</p>\n<p><strong>Key Responsibilities:</strong></p>\n<ul>\n<li>Design, supervise, and lead rodent in vivo mechanistic and disease models to support target identification, therapeutic candidate characterization, and mechanism of action evaluations.</li>\n<li>Lead multiple drug discovery programs, initiatives, or external collaborations in Research / Early Development (RED) CVRI.</li>\n<li>Provide expert opinion in Target ID teams or early research teams, offering disease-biology and in vivo model expertise.</li>\n<li>Act as disease biology lead in preclinical programs, ensuring excellence in biology and alignment with pharmacology-related deliveries.</li>\n<li>Support the strategic development of the &#39;In Vivo&#39; capability cluster and contribute to the drug development strategy of CVRI.</li>\n<li>Collaborate with other R&amp;D functions, support cross-team and cross-site activities, and contribute to key documentation and presentations.</li>\n<li>Employ VACC leadership principles to support management and coaching of research associates and junior scientists.</li>\n<li>Assess external targets and programs to understand the competitive landscape and identify opportunities for collaboration or technological innovation.</li>\n<li>Maintain and extend a network with external partners from academia, contract research organizations, and medical experts.</li>\n</ul>\n<p><strong>Requirements:</strong></p>\n<ul>\n<li>Ph.D. in Biology, Biochemistry, or a related life science field.</li>\n<li>Strong background in cardio-renal, with expertise in cardiovascular or metabolic space being highly advantageous.</li>\n<li>Demonstrated track record in drug discovery in a pharmaceutical or biotech setting.</li>\n<li>Deep knowledge and hands-on experience in designing and establishing translatable in vivo rodent disease models.</li>\n<li>Expertise in applying state-of-the-art in vivo models across the drug discovery process.</li>\n<li>Experience in strategic planning and project leadership.</li>\n</ul>\n<p><strong>Preferred Qualifications:</strong></p>\n<ul>\n<li>12+ years of relevant post-PhD experience, including 4+ years in industry.</li>\n<li>Proven record of successful drug discovery team leadership and interaction with collaborators.</li>\n</ul>\n<p><strong>Salary Range:</strong> $174,400.00 - $261,600.00</p>\n<p><strong>Benefits:</strong> Health care, vision, dental, retirement, PTO, sick leave, etc.</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_a93b4e02-fe7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Bayer","sameAs":"https://talent.bayer.com","logo":"https://logos.yubhub.co/talent.bayer.com.png"},"x-apply-url":"https://talent.bayer.com/careers/job/562949977738489?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$174,400.00 - $261,600.00","x-skills-required":["in vivo models","cardiovascular research","renal research","drug discovery","leadership"],"x-skills-preferred":["project management","strategic planning","team leadership"],"datePosted":"2026-06-23T22:12:37.639Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Boston, Massachusetts"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Healthcare","skills":"in vivo models, cardiovascular research, renal research, drug discovery, leadership, project management, strategic planning, team leadership","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":174400,"maxValue":261600,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2d4fb5a4-4ba"},"title":"Transformative AI Research Economist, Economic Research","description":"<p>As a Transformative AI Research Economist at Anthropic, you will build macroeconomic models of AI that could be genuinely transformative and develop scenario-based forecasting tools. 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models"],"datePosted":"2026-06-18T13:29:48.586Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Research","industry":"Technology","skills":"macroeconomics, growth theory, public finance, task-based frameworks, labor economics, Python, Julia, computational economics, AI coding agents, scenario-based forecasting, time-series forecasting, task-based approaches to technological change, computational methods, agent-based modeling, large-scale simulation, income distribution, inequality, large language models","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_37020b5d-785"},"title":"Insights Sr Researcher, PWS/C4C","description":"<p>The Insights Sr Researcher will 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