{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/jupyter-notebooks"},"x-facet":{"type":"skill","slug":"jupyter-notebooks","display":"Jupyter Notebooks","count":5},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_253a76ff-ceb"},"title":"Senior Machine Learning Engineer - Payments","description":"<p>We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products.</p>\n<p>Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Build with impact. Your work will empower millions of users through well-known and emerging Fintech Applications with access to financial services.</li>\n<li>Experiment with cutting edge ML modeling techniques.</li>\n<li>Work on both 0-1 stage problems as well as 1-10.</li>\n<li>Develop AI/ML models in a full life cycle, from offline training to online serving and monitoring.</li>\n<li>Collaborate with teams across Plaid to define ML roadmap.</li>\n<li>Dive deep into data and apply data driven decisions in day-to-day work.</li>\n<li>A high ownership, bottom-up driven team.</li>\n</ul>\n<p><strong>Qualifications</strong></p>\n<ul>\n<li>5+ years in training and serving AI/ML models in a production environment.</li>\n<li>Experience in building/working with data intensive backend applications in large distributed systems.</li>\n<li>Ability to code and iterate independently on top of data infrastructure tools like Python, Spark, Jupyter notebooks, standard ML libraries, etc.</li>\n<li>Take pride in taking ownership and driving projects to business impact.</li>\n<li>Data analytics and data engineering experience is a plus.</li>\n<li>Experience with the industry application of NLP is a plus.</li>\n<li>Experience with the FinTech industry is a plus.</li>\n<li>Ability to work with technical and non-technical teams</li>\n<li>Master&#39;s degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field.</li>\n</ul>\n<p><strong>Additional Information</strong></p>\n<p>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable.</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_253a76ff-ceb","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Plaid","sameAs":"https://plaid.com/","logo":"https://logos.yubhub.co/plaid.com.png"},"x-apply-url":"https://jobs.lever.co/plaid/b7d3a770-946b-4b08-92d3-e02506742066","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$228,960-344,160 per year","x-skills-required":["Python","Spark","Jupyter notebooks","standard ML libraries","data infrastructure tools","AI/ML models","machine learning","natural language processing","data analytics","data engineering"],"x-skills-preferred":["NLP","FinTech industry","data-intensive backend applications","large distributed systems"],"datePosted":"2026-04-17T12:50:59.773Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Finance","skills":"Python, Spark, Jupyter notebooks, standard ML libraries, data infrastructure tools, AI/ML models, machine learning, natural language processing, data analytics, data engineering, NLP, FinTech industry, data-intensive backend applications, large distributed systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":228960,"maxValue":344160,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cab4499b-7c8"},"title":"Senior Software Engineer, Scientific Computing","description":"<p>At KoBold we believe that a modern scientific computing stack will enable systematic mineral exploration and materially improve our rate of mineral discovery. This role is a key ingredient to this strategy. As a member of our scientific computing team, you will apply software engineering and machine learning to remote-sensing, drillhole, imaging, geophysics and other mineral exploration data in order to build scalable ML systems to help make high-speed, high-quality decisions for our mineral exploration projects. Collaborating with our exceptional team of data scientists and geologists, you will tackle complex scientific problems head-on and collectively pave the way for discoveries of vital energy transition metals like lithium, copper, nickel, and cobalt. Together we can shape the future of mineral exploration and contribute to building a sustainable world.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Architect, implement, and maintain foundational scientific computing libraries that will be used in KoBold’s mineral exploration analyses.</li>\n<li>Build tooling to increase the velocity of our machine learning progress, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&amp;D into robust, scalable ML pipelines; and organizing models and their outputs for repeatability and discoverability.</li>\n<li>In collaboration with data scientists, build models to make statistically valid predictions about the locations of economic concentrations of ore metals within the Earth’s crust.</li>\n<li>Apply–and coach team members to use–engineering best practices such as writing robust, testable and composable code</li>\n<li>Collaborate with data scientists, geoscientists and engineers to invent the modern scientific computing stack for mineral exploration</li>\n<li>Occasional travel to exploration sites around the world to observe the impact of scientific computing on KoBold’s exploration products and design new technologies to further discovery. Travel is approximately twice per year depending on project needs.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>At least 5 years of experience as a software engineer, data scientist or ML engineer, though most great candidates will have closer to 10.</li>\n<li>Track record of building production quality data processing solutions or tooling that have delivered business value</li>\n<li>Proficiency with foundational concepts of ML, including statistical, traditional and deep-learning approaches</li>\n<li>Proficiency in Python, ideally including array-based packages such as xarray and numpy</li>\n<li>Deep experience with measured scientific data</li>\n<li>Experience in visualizing scientific data for domain experts</li>\n<li>Experience in MLops and in the making of robust ML systems</li>\n<li>Drive to increase the velocity and effectiveness of our data scientists in both experimental and production workflows</li>\n<li>Capacity to dive deep on novel challenging problems in applying ML to mineral exploration, including understanding a complex domain of geology and mineral exploration practices as well as working with limited, disparate and noisy data sources</li>\n<li>Collaborative attitude to work with stakeholders with different backgrounds (data scientists, geoscientists, software engineers, operations)</li>\n</ul>\n<p>Work practices and motivation:</p>\n<ul>\n<li>Ability to take ownership and responsibility of large projects.</li>\n<li>Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain. Open to working directly with geologists in the field. Enjoys constantly learning such that you are driving insights and innovations.</li>\n<li>Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers. A strong communicator who enjoys working with colleagues across the company.</li>\n<li>Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities.</li>\n<li>Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company.</li>\n<li>Ability to independently prioritize multiple tasks effectively.</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_cab4499b-7c8","directApply":true,"hiringOrganization":{"@type":"Organization","name":"KoBold Metals","sameAs":"https://www.koboldmetals.com/","logo":"https://logos.yubhub.co/koboldmetals.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/koboldmetals/jobs/4624038005","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$170,000 - $215,000","x-skills-required":["Python","Machine Learning","Scientific Computing","Data Science","Geophysics","Remote Sensing","Drillhole Imaging","Jupyter Notebooks","MLops","Robust ML Systems"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:40:56.506Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Machine Learning, Scientific Computing, Data Science, Geophysics, Remote Sensing, Drillhole Imaging, Jupyter Notebooks, MLops, Robust ML Systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":170000,"maxValue":215000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3eca7e36-aa0"},"title":"Support Systems Architect","description":"<p><strong>Support Systems Architect</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><strong>Compensation</strong></p>\n<ul>\n<li>$216K – $240K • 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<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>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>The User Operations team is central to ensuring that our customers&#39; experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI&#39;s customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. Given OpenAI’s already breakneck shipping cadence – and the expectation that it will only accelerate – our ability to architect scalable systems for support readiness, user‑feedback, and broader program delivery is central to our ability to build world-class products and to maintain exceptional support quality.</p>\n<p><strong>About the Role</strong></p>\n<p>We are seeking a systems‑minded builder who will design, prototype, implement, and iterate on the tooling, data flows, and processes that allows the User Operations team to redefine a modern support organization. Think: automated launch checklists, content and knowledge pipelines, incident detection and evaluators, and other processes that power a User Operations team operating at an unprecedented scale. You’d be building resilient systems, not better slide decks.</p>\n<p>We’re looking for people who thrive at the intersection of project management, systems building, data science/data engineering/software engineering, team enablement, and customer advocacy – and enjoy working cross-functionally in a fast-paced, evolving environment.</p>\n<p>This role is based in San Francisco, California. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.</p>\n<p><strong>In this role you will:</strong></p>\n<ul>\n<li>Build “Day-1 enabled” workflows; role-tailored playbooks, content auto-diffs from source docs, and other workflows that have been taken for granted in typical Support organizations.</li>\n</ul>\n<ul>\n<li>Continuously automate repetitive touchpoints with scripts, agents, and LLM-powered flows; implement governance, observability, evaluation gates, and safe rollback.</li>\n</ul>\n<ul>\n<li>Codify detection (windowing, dedupe, thresholds), on-call handoffs, and post-incident learning loops that protect customer experience and SLAs.</li>\n</ul>\n<ul>\n<li>Prototype and learn quickly—leveraging ChatGPT, Jupyter notebooks, Retool, and other tools—to prove value before hardening with Engineering.</li>\n</ul>\n<ul>\n<li>Stand up data pipelines that capture sentiment, ticket trends, and BPO insights, routing actionable signals back to Product within hours—not weeks.</li>\n</ul>\n<ul>\n<li>Identify risks and challenges during tooling rollouts, proposing solutions that safeguard customer experience and service levels.</li>\n</ul>\n<ul>\n<li>Continuously automate, replacing every repetitive touchpoint with scripts, agents, or LLM-powered flows.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have 8+ years of experience in building tools for internal teams, especially within a customer support environment.</li>\n</ul>\n<ul>\n<li>Have shipped or maintained tools and automations (dashboards, ETL pipelines, low-code apps) that eliminated manual work and scaled beyond a single team.</li>\n</ul>\n<ul>\n<li>Treat ChatGPT &amp; LLMs as default co-developers, rapidly turning natural-language ideas into working code or queries.</li>\n</ul>\n<ul>\n<li>Deeply enjoy working cross-functionally and are skilled at building relationships with Product, Engineering, and Operations teams.</li>\n</ul>\n<ul>\n<li>Are passionate about customer advocacy and have experience translating customer feedback into strategic product insights.</li>\n</ul>\n<ul>\n<li>Possess a strong bias for automation and a distaste for doing low-complexity to otherwise repetitive work consistently.</li>\n</ul>\n<ul>\n<li>Thrive in a fast-moving, ambiguous environment where priorities will shift quickly and iterating on your systems will be required.</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 technologies like artificial intelligence benefit all of humanity.</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_3eca7e36-aa0","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/782db0f6-a03d-4f9f-9eb2-191831b37939","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216K – $240K • Offers Equity","x-skills-required":["ChatGPT","LLMs","Jupyter notebooks","Retool","project management","systems building","data science","data engineering","software engineering","team enablement","customer advocacy"],"x-skills-preferred":["automated launch checklists","content and knowledge pipelines","incident detection and evaluators","data pipelines","sentiment analysis","ticket trends","BPO insights"],"datePosted":"2026-03-06T18:36:31.397Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ChatGPT, LLMs, Jupyter notebooks, Retool, project management, systems building, data science, data engineering, software engineering, team enablement, customer advocacy, automated launch checklists, content and knowledge pipelines, incident detection and evaluators, data pipelines, sentiment analysis, ticket trends, BPO insights","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216000,"maxValue":240000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2916efa5-82d"},"title":"Data Scientist, Support","description":"<p><strong>Data Scientist, Support</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><strong>Compensation</strong></p>\n<ul>\n<li>$230K – $255K • 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<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>More details about our benefits are available to candidates during the hiring process.</p>\n<p><strong>About the Team</strong></p>\n<p>The User Operations team is central to ensuring that our customers&#39; experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI&#39;s customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. Given OpenAI’s breakneck shipping cadence and growth—and the expectation that it will only accelerate—transforming our rich support data into real‑time insights and scalable, self‑serve analytics is critical to sustaining exceptional customer experiences on the path to AGI.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re seeking a Support Data Scientist who will dig deep into user‑support data—surfacing trends, volumes, and friction signals—and turn these findings into actionable insights and always‑on reporting. You’ll design, build, and maintain self‑serve dashboards that keep every stakeholder informed in real time, partnering closely with Data Science and Engineering to ensure clean pipelines, robust models, and scalable tooling. Think proactive friction detection and real‑time service‑health views that help us stay ahead of demand—delivering decision‑grade insights, not just prettier slide decks.</p>\n<p>This role is based in San Francisco, California. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Explore large support and product datasets to uncover trends, volume drivers, and user‑experience pain points, distilling findings into clear, actionable narratives.</li>\n</ul>\n<ul>\n<li>Build, enhance, and maintain self‑serve dashboards and reporting tools, enabling non‑technical teams to answer their own data questions.</li>\n</ul>\n<ul>\n<li>Establish a unified metrics taxonomy for service‑health and performance—and build automated data‑sharing pipelines and scorecards with our BPO partners to ensure everyone operates from the same real‑time view of success</li>\n</ul>\n<ul>\n<li>Leverage LLMs to build bespoke classifiers that automatically label and segment inbound volumes—powering smarter routing, richer self‑serve insights, and swifter root‑cause analysis.</li>\n</ul>\n<ul>\n<li>Partner with Data Engineering to ensure reliable pipelines, implement data‑quality checks, and document sources of truth.</li>\n</ul>\n<ul>\n<li>Jump into high‑priority special projects to conduct bespoke deep‑dive analyses and deliver clear, strategic recommendations to leadership.</li>\n</ul>\n<ul>\n<li>Prototype quickly—leveraging ChatGPT, Jupyter notebooks, Retool, and other tools—to prove value before hardening with Engineering.</li>\n</ul>\n<ul>\n<li>Collaborate with Data Science on predictive models and experimentation, translating results into operational recommendations.</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>8 + years in analytics, business intelligence, or data science (experience with customer support or operations teams is a plus).</li>\n</ul>\n<ul>\n<li>Expert‑level SQL skills and proficiency in Python or R for advanced analysis and automation</li>\n</ul>\n<ul>\n<li>Hands‑on experience designing and maintaining BI dashboards (e.g. Looker, Mode, Tableau, Sundial) with a focus on clarity and self‑serve usability.</li>\n</ul>\n<ul>\n<li>Hands‑on experience fine‑tuning or prompt‑engineering LLMs to build text classifiers, sentiment analysis, or tagging systems.</li>\n</ul>\n<ul>\n<li>Demonstrated ability to translate complex datasets into clear business stories and recommendations for both technical and non‑technical audiences.</li>\n</ul>\n<ul>\n<li>Familiarity with support metrics (SLAs, FCR, deflection) and ability to define service health KPIs.</li>\n</ul>\n<ul>\n<li>Strong cross‑functional communication skills—comfortable collaborating daily with engineers, data scientists, and operations leaders.</li>\n</ul>\n<ul>\n<li>An eye for detail, a zero‑defect mindset, and a bias to</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_2916efa5-82d","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/1f37ae5b-791a-4505-9575-183cc4bb9d5e","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$230K – $255K","x-skills-required":["SQL","Python","R","BI dashboards","LLMs","Data Science","Data Engineering","Predictive models","Experimentation"],"x-skills-preferred":["ChatGPT","Jupyter notebooks","Retool","Looker","Mode","Tableau","Sundial"],"datePosted":"2026-03-06T18:32:13.138Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"SQL, Python, R, BI dashboards, LLMs, Data Science, Data Engineering, Predictive models, Experimentation, ChatGPT, Jupyter notebooks, Retool, Looker, Mode, Tableau, Sundial","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":255000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9bb2ce41-335"},"title":"Senior R&amp;D Engineer","description":"<p>You are a passionate and accomplished software engineer ready to take on complex technical challenges in a collaborative, forward-thinking environment. You thrive in fast-paced settings where innovation and quality are paramount. With a deep understanding of software architecture principles and hands-on experience in both legacy and modern development frameworks, you excel at designing, implementing, and optimizing solutions that address real-world problems.</p>\n<p><strong>What you&#39;ll do</strong></p>\n<p>Participating in the planning, architecture, and research phases for next-generation software products and systems.</p>\n<ul>\n<li>Leading complex development activities, including software design, solver research, and user experience enhancements.</li>\n</ul>\n<p><strong>What you need</strong></p>\n<p>Bachelor’s degree in Engineering, Computer Science, or related field with 5+ years of experience; Master’s with 3+ years; PhD with 1+ year.</p>\n<ul>\n<li>Expertise in software design and development methodologies, with commercial experience.</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_9bb2ce41-335","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Synopsys","sameAs":"https://careers.synopsys.com","logo":"https://logos.yubhub.co/careers.synopsys.com.png"},"x-apply-url":"https://careers.synopsys.com/job/vancouver/senior-r-and-d-engineer/44408/88397130176","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["software design and development methodologies","commercial experience","C++","Python","data structures and algorithms","REST APIs","Flask/Django","NodeJS","Jupyter Notebooks","Pandas","NumPy"],"x-skills-preferred":["Jupyter Notebooks","Pandas","NumPy"],"datePosted":"2025-12-22T12:00:54.853Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Vancouver"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software design and development methodologies, commercial experience, C++, Python, data structures and algorithms, REST APIs, Flask/Django, NodeJS, Jupyter Notebooks, Pandas, NumPy, Jupyter Notebooks, Pandas, NumPy"}]}