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market research & data analytics intern

software engineering intern (summer 2027) Jobs in San Francisco

ai ml intern

Encord

<div>
 <strong>
  About Us
  <br/>
  <br/>
 </strong>
 Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more.
 <br/>
 <br/>
 We're an ambitious team of 100+ working at the frontier of AI and have raised $110M in funding, including a Series C backed by Wellington Management, CRV, Next47, and Y Combinator.
 <br/>
 <br/>
 <strong>
  The role
  <br/>
  <br/>
 </strong>
 We're looking for a Senior Growth Manager to architect how technical buyers find, evaluate, and choose our platform &mdash; from first signal to closed deal. You'll own our demand generation strategy, building pipeline from target accounts within a defined vertical, deepening engagement with existing customers, and operating as a true partner to Sales. You'll lead a squad of three, setting direction, developing your team, and ensuring output connects directly to revenue.
 <br/>
 <br/>
 <strong>
  What You&rsquo;ll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Lead and develop your team &mdash; setting clear priorities, unblocking people, and maintaining a high bar for output across all growth programs
  </li>
  <li>
   Own pipeline strategy for target enterprise accounts &mdash; coordinating content, campaigns, outreach, and in-person touchpoints to drive qualified opportunities in partnership with Sales and SDRs
  </li>
  <li>
   Deploy AI agents to monitor account-level signals, identifying when target accounts are moving from cold to warm and surfacing the right moment for Sales to engage
  </li>
  <li>
   Use AI-driven intent tools at the contact level to flag high-intent prospects, inform personalisation, and help Sales prioritise outreach across an account
  </li>
  <li>
   Build and own our conference and field event strategy &mdash; identifying the right moments in the ML Ops, Data Ops, and AI infrastructure calendar, activating target accounts before and after events, and converting in-person presence into pipeline
  </li>
  <li>
   Develop co-marketing programs with technology partners across the ML Ops and AI infrastructure ecosystem, turning integrations and shared customers into joint campaigns and warm introductions into target accounts
  </li>
  <li>
   Work closely with AEs and Sales leadership to ensure Sales receives well-qualified, well-timed opportunities
  </li>
  <li>
   Manage lead routing, enrichment, and nurture tracks to reduce friction across enterprise buyer journeys
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Who we're looking for
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You're structured and precise in how you think about markets &mdash; you know how to map a landscape, identify where to focus, and build programs that convert that focus into pipeline
  </li>
  <li>
   You're energised by in-person relationship building &mdash; conferences, roundtables, and industry events are where you do some of your best work
  </li>
  <li>
   You're quick to pick up new tools and workflows &mdash; you're already using AI to work faster and smarter, and you're curious about where it goes next
  </li>
  <li>
   You can engage credibly on technical topics &mdash; ML infrastructure, compute orchestration, model evaluation, and developer tooling are areas you're motivated to go deep on
  </li>
  <li>
   You've managed or led small teams and know how to get the best out of people while keeping programs moving
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Experience requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3+ years in B2B growth, strategy, finance, or a commercially rigorous field &mdash; with a track record of owning outcomes, not just workstreams
  </li>
  <li>
   Direct experience in or exposure to the ML Ops, Data Ops, or AI infrastructure space, or adjacent areas such as model evaluation, robotics, physical AI, or autonomy
  </li>
  <li>
   Experience building and executing demand generation, field event, or co-marketing programs in a B2B environment
  </li>
  <li>
   Familiarity with AI-driven intent and signal tools (e.g. 6sense, Bombora, Clay) and how they integrate into a GTM motion
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Encord
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary, commission, and equity in a high-growth start-up
  </li>
  <li>
   Strong in-person culture - most of the team works from our London office 4+ days/week
  </li>
  <li>
   25 days annual leave + UK public holidays
  </li>
  <li>
   Annual learning &amp; development budget
  </li>
  <li>
   Travel for customer visits, events, and conferences across the UK and Europe
  </li>
  <li>
   Company lunches twice a week
  </li>
  <li>
   Monthly socials &amp; bi-annual team offsites
   <br/>
   <br/>
  </li>
 </ul>
</div>


Senior Growth Manager

Quantcast

<div><div>At Quantcast, we don't just build advertising technology, we revolutionize how it works. Our AI-powered Demand Side Platform (DSP) connects the world's most ambitious marketers with their ideal audiences across the open internet, delivering results that actually move the needle. Since 2006, we've been the industry's trailblazer, launching the first AI-powered measurement platform for publishers and the first AI-driven DSP. Our AI doesn't just optimize&mdash;it delivers the measurable outcomes that matter most to our clients, giving them the competitive edge they need in a crowded marketplace. Ready to join the team that's defining the future of digital advertising?</div><div></div><div><br>
The Modeling team is responsible for Machine Learning (ML) systems at Quantcast. We build and maintain multiple ML products that price millions of bid requests per second in a real-time auction environment to maximize advertiser outcomes. For each bid our models predict age, gender, viewability, fraud, advertiser relevance and many more characteristics. Using NLP, clustering and LLMs we build topics in multiple languages to help our advertisers target customers interested in relevant content.</div>
<div></div>
<div>As a Machine Learning Engineer you care about the health and maintainability of our systems and the velocity of the engineering teams. You explore data, research new algorithms, experiment with proof of concepts, and build out scalable real-time production systems to tackle challenges the company faces.</div>
<div></div>
<h3 class="jobSectionHeader"><b>What you'll do:</b></h3><ul>
<li>Design, code, test, and debug ML applications and constantly improve large-scale global systems that respond to millions of real-time requests per second efficiently.</li>
<li>Run Machine Learning experiments to test new modeling ideas.</li>
<li>Write clean, efficient, and maintainable code using industry best practices.</li>
<li>Collaborate closely with engineering teams, to deliver high-quality ML products. Participate in code reviews and provide constructive feedback to team members.</li>
<li>Identify performance bottlenecks and optimize system components for enhanced scalability.</li>
<li>Keep up to date with developments in machine learning outside the company.</li>
</ul><h3 class="jobSectionHeader"><b>Who you are:</b></h3><ul>
<li>New Grad to 1 year of experience.</li>
<li>You must be work-authorized in the United States without the need for employer sponsorship.</li>
<li>This is a hybrid role based in our San Francisco office. To ensure a manageable commute for in-office days, candidates must reside within a 60-mile radius of San Francisco, CA. No relocation candidates at this time.</li>
<li>Fluency in Python, Java or similar programming languages.</li>
<li>Strong skills in mathematics and statistics.</li>
<li>Working knowledge of ML algorithms such as classification, control systems, optimization, clustering, LLMs or recommendation systems.</li>
<li>An interest in distributed system and software design, concurrent algorithms, data structures, and software engineering.</li>
</ul><div>The expected base salary range for this role is $151,300 to $178,000.</div><div></div><div><br>
At Quantcast, we craft offers that reflect your unique skills, expertise, and geographic location. On top of a competitive salary, this position includes a performance bonus, equity, and a comprehensive benefits package. For more details, visit our Careers Page and see how we support our team. We are headquartered in San Francisco with offices around the world. Quantcast is an Equal Opportunity Employer. Please see the Applicant Privacy Notice for details on our applicant privacy policy. Join the team that unlocks potential.</div></div><div></div>

Machine Learning Engineer

Apple

<p>The Apple Services Engineering AI/ML organization is hiring a Machine Learning Engineer to join the Search team for Video catalog.<br>
<br>
Our team builds the core intelligence that powers search discovery experiences in the Apple TV App, Siri, and Spotlight cross platforms, helping users effortlessly find and enjoy the content they love. We are a collaborative, high-impact team that values innovation, craftsmanship, and end-to-end ownership from idea to launch. Our systems combine large-scale data, modern retrieval and ranking models, and a deep commitment to user privacy.<br>
<br>
Join us, you&rsquo;ll develop scalable systems and machine learning models that drive search relevance, personalization, and understanding of content at scale. Working closely with cross-functional partners in product and design, you&rsquo;ll translate cutting-edge research in advanced machine learning and generative AI into secure and delightful production features used by millions every day.<br>
<br>
<b>Description</b><br>
<br>
As a Machine Learning Engineer on the Video Search team, within the Apple Services Engineering AI/ML organization, you will design and deploy large-scale ML systems that power search and discovery across Apple platforms.<br>
<br>
You&rsquo;ll apply machine learning, natural language understanding, and generative AI to model user intent and deliver relevant, personalized results. Your work will involve building and optimizing cutting edge data processing, ML models, retrieval pipelines, and ranking systems that operate at global scale and under strict privacy standards.<br>
<br>
This is a hands-on role where you will collaborate closely with cross-functional teams to bring advanced ML technologies into production-shaping how users discovery content they love in Apple TV app, cross Apple TV partners on Apple Platforms, also through Siri and Spotlight.&quot;,&quot;responsibilities&quot;:&quot;Solve complex research problems and implement solutions from concept to execution.<br>
<br>
Design and implement retrieval and ranking systems using semantics and user context.<br>
<br>
Build and deploy ML, NLP and LLM models to improve search relevance and personalization.<br>
<br>
Analyze data and model performance to identify opportunities for search quality enhancement.<br>
<br>
Develop automated tests for continuous integration and ensure successful production deployment.<br>
<br>
Conduct A/B tests to measure search improvements.<br>
<br>
Collaborate with cross-functional teams to innovate intelligent video catalog text search.<br>
<br>
Enhance search recall and ranking for global Apple devices across all platforms and languages.<br>
<br>
Utilize big data tech to evaluate content discovery features.<br>
<br>
Ensure systems meet Apple&rsquo;s privacy, efficiency, and user experience standards.<br>
<br>
<b>Preferred Qualifications</b><br>
<br>
Experience with search or recommendation systems, and semantic retrieval or vector databases.<br>
<br>
Expertise in transformer architectures, embeddings, and retrieval or ranking models.<br>
<br>
Experience in applying or fine-tuning LLMs for understanding and generation tasks. Familiarity with prompt design, context management, RAG and Agentic architectures and solutions.<br>
<br>
Exposure to evaluation and safety frameworks for LLM-based systems.<br>
<br>
Knowledge of reinforcement learning and other modern post training practices for LLMs.<br>
<br>
Passion for developing intelligent, human-centered experiences to enhance content discovery.<br>
<br>
<b>Minimum Qualifications</b><br>
<br>
Experience in machine learning, NLP, IR, or more recently Large Language Model ( LLMs).<br>
<br>
Strong programming skills in Python, Java and Go for building scalable ML systems.<br>
<br>
Hands-on expertise in ML libraries such as PyTorch, JAX, TensorFlow for model training and deployment.<br>
<br>
Ability to translate product goals into technical solutions, improving user experience.<br>
<br>
Strong communication, collaboration, and analytical problem-solving skills.<br>
<br>
In-depth knowledge of search and information retrieval fundamentals, including indexing and ranking. Experience with retrieval and ranking algorithms and building big data pipelines using Hadoop, Java, Scala, Spark and more.<br>
<br>
Industrial experience in search, classification, recommendation systems, or related fields.<br>
<br>
Familiarity with A/B testing and data-driven product development.<br>
<br>
Passionate about creating products loved by customers at Apple.<br>
<br>
Bachelor&rsquo;s degree or higher (or equivalent practical experience) in Computer Science, Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field.<br>
<br>
<b>Pay &amp; Benefits</b><br>
<br>
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.<br>
<br>
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits<br>
<br>
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

Machine Learning Engineer, ASE Search Team

Workato

<div><div><h1 class="jobSectionHeader"><b>About Workato</b></h1>
<p>
Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato&rsquo;s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com</p>
<h1 class="jobSectionHeader"><b>
Why join us?</b></h1>
<p>
Ultimately, Workato believes in fostering a <b>flexible, trust-oriented culture that empowers everyone to take full ownership of their roles</b>. We are driven by <b>innovation </b>and looking for<b> team players </b>who want to actively build our company.</p>
<p>
But, we also believe in <b>balancing productivity with self-care</b>. That&rsquo;s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.</p>
<p>
If this sounds right up your alley, please submit an application. We look forward to getting to know you!</p>
<p>
Also, feel free to check out why:</p>
<ul>
<li><p>Business Insider named us an &ldquo;enterprise startup to bet your career on&rdquo;</p>
</li>
<li><p>Forbes&rsquo; Cloud 100 recognized us as one of the top 100 private cloud companies in the world</p>
</li>
<li><p>Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America</p>
</li>
<li><p>Quartz ranked us the #1 best company for remote workers</p>
</li>
</ul></div><div><h2 class="jobSectionHeader"><b>Senior AI Engineer &ndash; Developer Products</b></h2>
<p><b>
Location:</b> San Francisco, CA (Onsite/Hybrid)</p>
<h3 class="jobSectionHeader"><b>
About the Role</b></h3>
<p>
We are seeking an exceptional <b>Senior Software Engineer</b> to join our San Francisco team and build new developer products. In this role, you will design, build, and optimize AI-first experiences that empower developers to experiment, prototype, and integrate with our platform. You will collaborate closely with product, engineering, and developer relations teams to deliver robust, scalable, and intuitive services. This role requires a high technical bar, plus an emphasis on developer ergonomics, so we can deliver a delightful developer experience.</p>
<h3 class="jobSectionHeader"><b>
Responsibilities</b></h3>
<ul><li><b>Design, build, and enhance</b> AI services and APIs powering our developer sandbox, leveraging LLMs and custom ML models.</li>
<li><b>Develop well-architected, testable, and efficient Python code</b> to support rapid prototyping and experimentation.</li>
<li><b>Implement and improve validation, monitoring, and observability</b> for ML services within the sandbox environment.</li>
<li><b>Drive the full development lifecycle</b>: from ideation and architecture to deployment and continuous improvement.</li>
<li><b>Collaborate with cross-functional teams</b> to design developer-centric solutions and intuitive user experiences.</li>
<li><b>Continuously evaluate and optimize</b> existing implementations for performance, scalability, and developer usability.</li>
<li><b>Identify and resolve bottlenecks, bugs, and technical challenges</b> in a fast-paced, iterative environment.</li>
<li><b>Conduct code reviews</b> and mentor team members to uphold high engineering standards.</li>
</ul><h3 class="jobSectionHeader"><b>Requirements</b></h3>
<h4 class="jobSectionHeader"><b>Qualifications / Experience / Technical Skills</b></h4>
<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience.</li>
<li><b>5+ years of experience</b> as an ML Engineer, Data Scientist, or similar role.</li>
<li><b>Strong Python programming skills</b> and hands-on experience with NLP and LLM models.</li>
<li>Proven track record of <b>deploying and maintaining ML services in production</b> environments.</li>
<li>Solid understanding of <b>network protocols, API design, and developer tooling</b>.</li>
<li>Experience with <b>relational and non-relational databases</b>.</li>
<li><b>LLMops/MLops experience</b> is a strong plus, especially in developer-facing products.</li>
<li>Experience building or supporting <b>developer platforms, APIs, or sandbox environments</b> is highly desirable.</li>
</ul><h4 class="jobSectionHeader"><b>Soft Skills / Personal Characteristics</b></h4>
<ul><li>Collaborative team player with a passion for empowering developers and improving developer experience.</li>
<li>Adaptable, proactive, and creative&mdash;comfortable working in a dynamic, startup-like environment.</li>
<li>Strong problem-solving skills and a continuous improvement mindset.</li>
</ul>
<p><b>Join us in San Francisco and help shape the future of developer innovation with AI-powered sandbox experiences!</b><br>
<br>
The salary range for this role is dependent on experience and ranges from $170,000 to $250,000. We also provide stock options to all employees and generous benefits.</p></div></div>

Senior AI Engineer – Developer Products

reddit

<div><div><div><div><div><div><div><div>Reddit is a community of communities. It's built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet's largest sources of information. For more information, visit www.redditinc.com.</div>
</div>
</div></div></div></div></div><p><b>Team overview:</b></p>
<p>
The Engagement Modeling Team at Reddit focuses on building machine learning models to drive on-platform user engagement with diverse media and content, with a focus on predictive modeling to improve interactions of click-throughs and video view-throughs. This role offers a unique opportunity to shape and scale Reddit's Ads prediction models, in alignment with our product goals and driving SoTA modeling advancement.</p>
<p>
This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders.</p>
<p>
We're a remote-friendly company, and this position is open to candidates anywhere in the U.S.</p>
<p><b>
Responsibilities:</b></p>
<ul>
<li><b>Set Technical Vision and Strategy:</b> Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives.</li>
<li><b>Drive Technical Execution:</b> Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.</li>
<li><b>Lead and Mentor a High-Performing Team:</b> Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.</li>
<li><b>Collaborate Cross-Functionally:</b> Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.</li>
<li><b>Innovate in ML Architecture:</b> Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques.</li>
</ul>
<p><b>Candidate Profile:</b></p>
<p>
The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have:</p>
<ul>
<li><b>People Management Experience:</b> Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.</li>
<li><b>Set Technical Vision and Strategy:</b> Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.</li>
<li><b>Drive Technical Execution:</b> Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.</li>
<li><b>Lead and Mentor a High-Performing Team:</b> Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.</li>
<li><b>Collaborate Cross-Functionally:</b> Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.</li>
<li><b>Innovate in ML Architecture:</b> Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.</li>
</ul>
<p><b>Required qualifications:</b></p>
<ul>
<li>At least 2+ of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well</li>
<li>Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems. Proven ability in training, evaluating, and deploying large-scale models.</li>
<li>End-to-End ML Lifecycle Experience: Proven ability in training, evaluating, and deploying large-scale models.</li>
<li>4+ years of hands-on experience with TensorFlow or PyTorch.</li>
<li>Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy that supports broader company objectives and addresses the needs of internal customers.</li>
<li>Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.</li>
<li>Exceptional Communication &amp; Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners</li>
</ul><ul><li><b>Experience with Ads or Engagement Modeling is a plus.</b></li>
</ul>
<p><b>Perks and Benefits:</b></p>
<ul>
<li>100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)</li>
<li>Competitive salary and equity options</li>
<li>Comprehensive health benefits (medical, dental, vision) &amp; workplace perks (home office set up stipend etc)</li>
<li>Generous 401k matching</li>
<li>Flexible vacation policy</li>
<li>Paid parental leave (4+ months)</li>
<li>Family planning support</li>
<li>Paid volunteer time off</li>
</ul>
<p>#LI-AS1</p><p></p><div><p><br>
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.</p>
<p>
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.</p>
<p><i>
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.</i></p></div></div>

Machine Learning Engineering Manager - Ads Engagement Modeling

Plaid

<div><div><h2 class="jobSectionHeader"><b>Location</b></h2>
<p>San Francisco HQ; New York City Office; Seattle Office</p>
</div><div><h2 class="jobSectionHeader"><b>Address</b></h2>
<p>1098 Harrison Street, San Francisco, California, 94103</p>
</div><div><h2 class="jobSectionHeader"><b>Employment Type</b></h2>
<p>Full time</p>
</div><div><h2 class="jobSectionHeader"><b>Location Type</b></h2>
<p>Hybrid</p>
</div><div><h2 class="jobSectionHeader"><b>Department</b></h2>
<p>All DepartmentsData</p>
</div><div><h2 class="jobSectionHeader"><b>Compensation</b></h2>
<ul><li>$211,680 &ndash; $272,160</li>
</ul><div><p>Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.</p></div></div></div>
<br><div><div><p>We believe that the way people interact with their finances will drastically improve in the next few years. We&rsquo;re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. 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. Plaid&rsquo;s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.</p>
<p>The Data Foundation &amp; AI team sits within Plaid&rsquo;s Data organization and is responsible for building the shared machine learning and AI infrastructure that powers innovation across Plaid&rsquo;s product portfolio. The team transforms Plaid&rsquo;s unique financial network data into scalable, general-purpose representations that can be leveraged by teams throughout the company. Working across the full model lifecycle, the team develops and curates pretraining datasets, trains and evaluates foundation models, and operates production-grade serving and monitoring systems to ensure reliable, high-impact AI capabilities at scale.</p>
<p></p><p>As a Research Scientist, you will advance Plaid&rsquo;s foundation models by developing novel model architectures, pretraining objectives, and fine-tuning strategies that generalize across a broad range of financial and product applications. You will contribute to the design, development, and operation of production machine learning systems, working across the full stack from data and feature engineering to training pipelines, model serving, and monitoring. The role also involves creating comprehensive evaluation frameworks that assess model performance across diverse tasks and use cases, ensuring robust and reliable outcomes. In close partnership with product and engineering teams, you will adapt foundation models to solve specific business challenges, validate their impact through rigorous experimentation, and translate research advances into production capabilities. You will also share insights and results with both internal and external audiences, helping drive innovation and elevate the practice of machine learning and AI across Plaid.</p>
<p></p><p>Responsibilities:</p>
<ul><li><p>Building a foundation model on one of the world&rsquo;s richest financial datasets that no one else has.</p>
</li><li><p>Doing research that ships: moving from experimentation and prototypes to production systems serving real customers.</p>
</li><li><p>Working across the full ML stack, from pretraining objectives and architectures to serving infrastructure and monitoring.</p>
</li><li><p>Collaborating with a high-caliber team and seeing your work amplify the capabilities of multiple product teams.</p>
</li><li><p>Helping hundreds of millions of consumers achieve greater financial freedom through data-driven products.</p>
</li></ul><p>Qualifications:</p>
<ul><li><p>MS or PhD in ML/AI/CS/Stats/Applied Math (or closely related). PhD preferred but not required &mdash; candidates with equivalent industry research and production experience will be considered.</p>
</li></ul><ul><li><p>1-3 years of industry experience building and deploying ML models, with evidence of both research depth and production delivery</p>
</li><li><p>Strong applied ML research skills with production delivery experience</p>
</li><li><p>Depth in Transformers/LLMs, representation learning, or large-scale model training</p>
</li><li><p>Distributed training experience and strong Python + software engineering fundamentals</p>
</li><li><p>Fintech / financial data domain experience - Nice to have</p>
</li><li><p>Demonstrated ability to ship models to production (not just prototype) - Nice to have</p>
</li><li><p>External publications or open-source contributions - Nice to have</p>
</li></ul><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. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!</p>
<p>Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.</p><br>
<p></p>
<p>Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.</p>
Compensation Range: $211,680 - $272,160</div></div><p></p>

Machine Learning Engineer (Research Scientist) - DFAI

Anthropic

<div><div><h2 class="jobSectionHeader"><b>About Anthropic</b></h2>
<p>
Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><div><h2 class="jobSectionHeader"><b>
About the role</b></h2>
<p>
The Research Data Platform team builds the tools that Anthropic's researchers use every day to manage, query, and analyze the data that goes into training and evaluating frontier models. We power the internal applications researchers rely on to monitor RL runs, explore finetuning datasets, and understand what's happening inside their experiments.</p>
<p>
We're looking for engineers who love working directly with users and who excel at building data products &mdash; the pipelines that move data out of training runs into queryable storage, and the APIs, libraries, and services researchers use to manage and explore it. This role sits closer to the research workflow than a typical data infrastructure position: you'll often embed with research teams, build ML-specific tooling alongside them, and leverage what our Data Infrastructure team has already built rather than reinventing it.</p>
<p>
We do not require prior ML or AI training experience. If you enjoy working closely with technical users, learning new domains quickly, and building tools people actually want to use, you'll pick up the research context fast.</p>
<h2 class="jobSectionHeader"><b>
Responsibilities</b></h2>
<ul><li>Build and operate data pipelines that extract data from research training runs and land it in storage systems that are easy and fast to query</li>
<li>Work closely with researchers to design and build APIs, libraries, and web interfaces that support data management, exploration, and analysis</li>
<li>Develop dataset management, data cataloging, and provenance tooling that researchers use in their day-to-day work</li>
<li>Embed with research teams to understand their workflows, identify high-leverage tooling opportunities, and ship solutions quickly</li>
<li>Collaborate with adjacent teams to build on existing systems rather than reinventing them</li>
</ul><h2 class="jobSectionHeader"><b>You may be a good fit if you</b></h2>
<ul><li>Have significant software engineering experience, particularly building data-intensive applications or internal tooling</li>
<li>Enjoy working directly with users, gathering requirements iteratively, and shipping things that get adopted</li>
<li>Are results-oriented, with a bias towards flexibility and impact</li>
<li>Pick up slack, even if it goes outside your job description</li>
<li>Want to learn more about machine learning research</li>
<li>Care about the societal impacts of your work</li>
</ul><h2 class="jobSectionHeader"><b>Strong candidates may also have experience with</b></h2>
<ul><li>Large-scale ETL, columnar storage formats, and query engines (e.g., Spark, BigQuery, DuckDB, Parquet)</li>
<li>High-volume time series data &mdash; ingestion, storage, and efficient querying</li>
<li>Data cataloging, lineage, or metadata management systems</li>
<li>ML experiment tracking or metrics platforms</li>
<li>Working in environments where engineers partner closely with quantitative users &mdash; research labs, trading firms, observability or analytics startups</li>
<li>Complex data visualization and full-stack web application development</li>
</ul></div><div><div><div><div><p>
The annual compensation range for this role is listed below.</p>
<p>
For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p></div></div><p>
Annual Salary:</p><p>
$320,000 - $405,000 USD</p></div></div><div><h2 class="jobSectionHeader"><b>
Logistics</b></h2>
<p><b>
Minimum education: </b>Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience</p>
<p><b>
Required field of study: </b>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><b>
Minimum years of experience: </b>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><b>
Location-based hybrid policy:</b> Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>
<p><b>
Visa sponsorship:</b> We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>
<p><b>
We encourage you to apply even if you do not believe you meet every single qualification.</b> Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.<br>
<br>
<b>Your safety matters to us.</b> To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.</p>
<h2 class="jobSectionHeader"><b>
How we're different</b></h2>
<p>
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>
<p>
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2 class="jobSectionHeader"><b>
Come work with us!</b></h2>
<p>
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. <b>Guidance on Candidates' AI Usage:</b> Learn about our policy for using AI in our application process.</p></div></div>

Software Engineer, Research Data Platform

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