{"schemaVersion":"jobsearcher.job.v1","id":"9cd84330a4f077a67603d206","url":"https://jobsearcher.com/jobs/9cd84330a4f077a67603d206","canonicalUrl":"https://jobsearcher.com/jobs/9cd84330a4f077a67603d206","title":"Machine Learning Engineer","description":"Machine Learning Engineer\r\nLocation: San FranciscoAbout the Team\r\nOur client is a leading private equity firm with a dedicated AI team that works directly with portfolio company leadership and the investment team to identify, size, and deliver applied AI opportunities. The team runs like a small, fast-moving internal product shop, shipping pragmatic tools and automations in weeks rather than running enterprise software projects measured in quarters.The Role\r\nThey're looking for a builder: someone who can take a rough, high-value idea (an automation, an internal copilot, a data pipeline that turns a recurring manual analysis into a repeatable tool) and ship it end-to-end. You'll work shoulder-to-shoulder with the team's data scientists and directly with portfolio company and investment team stakeholders, not off a backlog of tickets handed down from a PM.What You'll DoDesign and build internal tools, automations, and data pipelines that scale the team's analyses across a broad portfolioDevelop applied AI / LLM-powered workflows, such as agents or copilots that automate recurring diligence, reporting, or analytical tasksPartner with the data scientists to take models and analyses from prototype to production-grade toolIntegrate with internal and external data sources and systems as neededHelp set a pragmatic, ship-fast engineering culture suited to a small, high-leverage team rather than a large engineering orgWhat You'll Bring2-3 years in a technical/build capacity at a top-tier consulting firm (e.g. the technology arms of the major strategy consultancies), or 2-3 years as a software engineer with exposure to fast-paced, stakeholder-facing deliveryStrong full-stack or backend engineering skills, with Python requiredComfort with modern data infrastructure: SQL, cloud data warehouses, APIsA genuine product ownership mentality, comfortable scoping, building, shipping, and iterating on a tool with minimal hand-holdingComfort working directly with non-technical business stakeholders to turn a rough idea into a working solutionStrong data analysis skillsExperience building end-to-end applications with foundation and open-weight LLMs: agents, copilots, and automation workflowsCuriosity and a willingness to learnNice to HaveExposure to private equity, consulting, or portfolio operationsExperience building data pipelines that integrate financial, operational, or workforce data across multiple companiesExperience with additional languages such as Rust or GoWhy This Role\r\nIt's a small, high-leverage team, and your code goes straight into decisions that move real capital rather than onto a roadmap. You own things end-to-end, in an environment that moves at deal speed.Burns Sheehan Ltd will consider applications based only on skills and ability and will not discriminate on any grounds.#J-18808-Ljbffr","company":"Burns Sheehan","rawCompany":"burns sheehan","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-11-04T02:02:59.991Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"Machine Learning Engineer\r\nLocation: San FranciscoAbout the Team\r\nOur client is a leading private equity firm with a dedicated AI team that works directly with portfolio company leadership and the investment team to identify, size, and deliver applied AI opportunities. 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You'll work shoulder-to-shoulder with the team's data scientists and directly with portfolio company and investment team stakeholders, not off a backlog of tickets handed down from a PM.What You'll DoDesign and build internal tools, automations, and data pipelines that scale the team's analyses across a broad portfolioDevelop applied AI / LLM-powered workflows, such as agents or copilots that automate recurring diligence, reporting, or analytical tasksPartner with the data scientists to take models and analyses from prototype to production-grade toolIntegrate with internal and external data sources and systems as neededHelp set a pragmatic, ship-fast engineering culture suited to a small, high-leverage team rather than a large engineering orgWhat You'll Bring2-3 years in a technical/build capacity at a top-tier consulting firm (e.g. the technology arms of the major strategy consultancies), or 2-3 years as a software engineer with exposure to fast-paced, stakeholder-facing deliveryStrong full-stack or backend engineering skills, with Python requiredComfort with modern data infrastructure: SQL, cloud data warehouses, APIsA genuine product ownership mentality, comfortable scoping, building, shipping, and iterating on a tool with minimal hand-holdingComfort working directly with non-technical business stakeholders to turn a rough idea into a working solutionStrong data analysis skillsExperience building end-to-end applications with foundation and open-weight LLMs: agents, copilots, and automation workflowsCuriosity and a willingness to learnNice to HaveExposure to private equity, consulting, or portfolio operationsExperience building data pipelines that integrate financial, operational, or workforce data across multiple companiesExperience with additional languages such as Rust or GoWhy This Role\r\nIt's a small, high-leverage team, and your code goes straight into decisions that move real capital rather than onto a roadmap. You own things end-to-end, in an environment that moves at deal speed.Burns Sheehan Ltd will consider applications based only on skills and ability and will not discriminate on any grounds.#J-18808-Ljbffr","datePosted":"2026-11-04T02:02:59.991Z","dateModified":"2026-11-04T02:02:59.991Z","hiringOrganization":{"@type":"Organization","name":"Burns Sheehan","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"9cd84330a4f077a67603d206"},"url":"https://jobsearcher.com/jobs/9cd84330a4f077a67603d206"}}