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applied robotics engineer san francisco ca

Smvsoft LLC

<p><b>Founding Engineer - Applied AI</b><br/>San francisco, CA (Full time)- In-Office</p><p>$180k-$230k per annum</p><p><b>NO C2C</b></p><p><b>About the Role</b></p><p>Hiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering.</p><p>This is a deeply technical, high-impact role. You will be among the first technical hires and will own mission-critical systems end-to-end. The problems are ambiguous, the constraints are real, and the expectations are high. If you move fast from idea to production, care deeply about customer experience, and want to build foundational AI infrastructure for the world's most impactful industries, this role is for you.</p><p><b>Key Responsibilities</b></p><ul><li>Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches, and post-training</li><li>Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems</li><li>Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments</li><li>Prototype rapidly, validate ideas with real users, and ship frequently</li><li>Influence engineering culture, architecture decisions, and the future of the product</li></ul><p><b>Requirements</b></p><p><b>Must-Have</b></p><ul><li>Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience</li><li>Strong familiarity with LLM architectures and agent research trends</li><li>Excellent programming skills with experience using ML libraries such as PyTorch, Hugging Face, and W&amp;B</li><li>Experience building production ML or AI systems</li><li>Solid practical experience with search and information retrieval</li><li>Moves fast from idea to production, with a genuine care for customer experience</li><li>Based in or willing to relocate to San Francisco, or an exceptional remote candidate</li></ul><p><b>Nice-to-Have</b></p><ul><li>2+ years in applied machine learning, backend engineering, or AI infrastructure</li><li>Experience working with machine learning over geometric data, including CAD</li><li>Track record of high-impact contributions or published papers at top-tier AI labs or teams</li></ul><p>Pay: $180,000.00 - $230,000.00 per year</p><p>Work Location: In person</p>

Founding Engineer - Applied AI

Youtube

<div><p>This role may also be located in our Playa Vista, CA campus.</p><p>
Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.</p><p>
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.</p><br>
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: <b>New York, NY, USA; Atlanta, GA, USA; Chicago, IL, USA; Mountain View, CA, USA; Los Angeles, CA, USA; San Bruno, CA, USA; San Francisco, CA, USA</b>.<h3 class="jobSectionHeader"><b>
Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree or equivalent practical experience.<br>
</li>
<li>10 years of experience in advertising, marketing technology, management consulting, or product management.<br>
</li>
<li>2 years of experience managing individuals and leading cross-functional teams.<br>
</li>
<li>Experience leading operational initiatives.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Experience in Google&rsquo;s ad solutions and value proposition in the market, and creative ads products and generative AI.</li>
<li>Ability to manage multiple projects and stakeholders, as well as influence and drive results without official authority.</li>
<li>Ability to operate and drive clarity in a fast moving and ambiguous space, and to navigate large complicated organizations.</li>
<li>Ability to influence product leadership through development of strategic programming and event execution that focuses on showcasing strategic priorities and key pain points.</li>
<li>Excellent problem solving and analytical skills, with the ability to provide data driven insights to shape strategy and key decisions.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
This role sits in the YouTube Ads GTM team with a mission to fuel innovation that keeps YouTube and Video free and accessible to the world by effectively monetizing YouTube with advertisers. The Creative team's mission is to accelerate advertisers and partners' ability to create more effective ads that will drive their business objectives and grow Google/YouTube investment. The team plays a vital role in empowering advertisers and partners with the creative solutions and resources they need to be set up for success across the Ads platforms.</p><p>
As the Senior Manager, you will lead a team focused on first-party creative products for the YouTube and Video ad solutions while also driving cross-GPS creative efforts to ensure a cohesive customer experience. In this role, you will work collaboratively with stakeholders across GPS, Product, Marketing, gTech, GTM, and Sales to ensure Creative offerings meet the needs of our advertisers while also driving commercialization strategy and execution globally.</p><p></p>
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
<br>
<br>
US: $186000 - $270000 (USD) + 20% bonus target + equity + benefits<br>
<br>
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Partner with Product and Engineering to shape the roadmap for emerging creative solutions, vetting product-market fit and ensuring alignment with YouTube Ads' strategic goals.</li>
<li>Build strategic business cases for innovations by leveraging customer needs and market trends to prioritize features that solve real-world advertiser pain points.</li>
<li>Lead go-to-market strategy for YouTube/Google Creatives, managing early-stage pilots and translating complex features into clear business motions that empower global teams.</li>
<li>Serve as the primary market feedback channel, leading test and learn incubation phases and synthesizing data from pilots to iterate before global scaling.</li>
<li>Lead high-performing ICs and orchestrate alignment across Sales, Marketing, Legal, and PR to ensure a unified approach to launching new creator solutions.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Manager, Creative Solutions, YouTube Ads GTM

Hellyeah AI

<p><b>AI Engineer - Learn Engine: Intelligence &amp; Optimization</b></p><p>Location: San Francisco HQ; Shanghai</p><p>Address: San Francisco, California</p><p>Employment Type: Full time</p><p>Location Type: Hybrid</p><p>Department: Engineering</p><p>Compensation: San Francisco $200K - $1M + 0.5% - 3% equity</p><p>Build the brain of an autonomous growth OS. The system you create will manage millions in ad spend and get measurably smarter with every dollar. This is the moat: every competitor has humans optimizing campaigns manually. You are building the intelligence layer that compounds. The Platform engineer creates the tools; you create the decisions. Together you build something nobody else has.</p><p>Must Have</p><p>- Has built recommendation, optimization, or decision systems where outputs improve future inputs.</p><p>- Strong statistical reasoning and experimentation judgment under noisy real-world data.</p><p>- Strong LLM orchestration or agent-system experience for reasoning over campaign context.</p><p>- Can design optimization policies, scoring systems, or automated recommendation loops.</p><p>- AI-first development workflow and ability to ship production systems quickly.</p><p>Nice to Have</p><p>- Ad-tech optimization patterns: bid management, budget allocation, ROAS optimization.</p><p>- Reinforcement learning experience.</p><p>- Hyperparameter optimization experience.</p><p>- Model fine-tuning experience.</p><p>- Experience building agent-driven automation where LLM agents take actions.</p><p>- Background in growth engineering, performance marketing, or data science.</p><p>- Experience with Mastra or similar agent orchestration framework.</p><p>What You Will Own</p><p>Own the intelligence and optimization layer of Learn Engine. Build recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization. Turn SSOT campaign data into high-quality optimization guidance and closed-loop decision systems. Define how the system learns from outcomes and continuously improves campaign strategy over time. This role owns decision quality, optimization policy, and learning loops, not platform plumbing or simulator infrastructure.</p><p>Pay: $200,000.00 - $1,000,000.00 per year</p><p>Work Location: In person</p>

AI Engineer - Learn Engine: Intelligence & Optimization

David Joseph & Company

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $120,000&ndash;$300,000 + Competitive Equity</p><h2 class="jobSectionHeader"><b>
About the Company</b></h2><p>
An early-stage, venture-backed FinTech building AI compliance analysts that automate AML, KYC, KYB, and transaction monitoring end-to-end for banks and fintechs. The product operates inside browsers, APIs, and internal systems the way a human analyst would, and is already live with financial institutions across multiple regions.</p><p>
Founded 2024 &middot; Seed stage &middot; Small team &middot; Industry: FinTech</p><h2 class="jobSectionHeader"><b>
The Role</b></h2><p>
A backend-leaning Member of Technical Staff building the end-to-end systems that power production AI compliance workflows &mdash; high-performance infrastructure, reliability, and backend architecture supporting mission-critical automation.</p><p><b>
What you'll be doing</b></p><ul><li>
Architect agent behaviors and build the backend systems behind production AI compliance workflows</li><li>
Build browser agents that navigate legacy systems, portals, and third-party platforms, interpreting unstructured data</li><li>
Process risk signals at the speed money moves &mdash; millions of transactions, sub-second decisions &mdash; via distributed inference, caching, queue orchestration, and self-healing data pipelines on AWS</li><li>
Contribute to an in-house deep-research pipeline that keeps LLMs from conflating similar entities</li><li>
Optimize ML pipelines and ship product features, owning problems vertically</li></ul><p><b>
Tech stack:</b> Python, AWS; browser automation, computer vision, LLM systems.</p><h2 class="jobSectionHeader"><b>
Requirements</b></h2><ul><li>
Experience with backend development and/or ML, especially in Python and AWS</li><li>
Hands-on experience deploying software to production environments</li><li>
Strong communication skills and willingness to interact with clients</li></ul><h2 class="jobSectionHeader"><b>
Green Flags</b></h2><ul><li>
Experience with browser automation and computer vision</li><li>
Background with distributed inference and optimization on AWS</li><li>
Familiarity with LLM systems and deep research pipelines</li><li>
Experience building systems that process millions of transactions at scale</li><li>
Knowledge of compliance, AML, KYC, or financial crime domains</li><li>
Competitive coding background</li><li>
Contributions to open-source projects or personal projects on GitHub</li><li>
Prior experience as a founder or at an early-stage startup</li></ul><h2 class="jobSectionHeader"><b>
Red Flags</b></h2><ul><li>
Candidates from a pure data science background who lack strong technical skills</li><li>
Lack of hands-on experience deploying software to production</li><li>
Primarily academic or research experience without practical engineering work</li></ul><h2 class="jobSectionHeader"><b>
Why Join</b></h2><ul><li>
Build frontier AI agents in production, solving hard problems with no off-the-shelf answers</li><li>
Large, underserved market with real customer traction and measurable impact</li><li>
Small team with wide surface area &mdash; own features end-to-end across backend, ML, and product</li></ul><h2 class="jobSectionHeader"><b>
Details</b></h2><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site</li><li><b>
Compensation:</b> $120,000&ndash;$300,000 + equity</li><li><b>
Visa sponsorship:</b> H-1B, O-1, OPT</li><li><b>
Experience:</b> 1+ years</li><li><b>
Employment type:</b> Full-time</li></ul></div>

Member of Technical Staff

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $180,000&ndash;$220,000 + competitive equity</p><h2 class="jobSectionHeader"><b>
About the Company</b></h2><p>
An early-stage (post&ndash;Series A) company building the training data and evaluation infrastructure that frontier AI labs use to improve their models &mdash; designing high-signal datasets and running rigorous evaluations that go beyond static benchmarks. A small team where individual contributors have direct impact on how the next generation of models learns. The company has raised $30M (~$300M valuation), with a founding team drawn from Jane Street, Citadel, Google, Goldman, and Stanford AI Lab.</p><p>
Founded 2025 &middot; 11&ndash;50 people &middot; Industry: Consumer Tech</p><h2 class="jobSectionHeader"><b>
The Role</b></h2><p>
As a SWE (Environments), you'll design the datasets and evaluation rubrics that directly influence how frontier models learn &mdash; going from hypothesis to live experiment quickly, with output feeding directly into model training runs at scale.</p><p><b>
What you'll be doing</b></p><ul><li>
Design data slices and explore data shapes that expose meaningful model failure modes across domains like finance, code, and enterprise workflows</li><li>
Build and refine evaluation rubrics and reward signals for RLHF and RLVR training pipelines</li><li>
Model annotator behavior and run experiments to improve different model capabilities</li><li>
Develop quantitative frameworks for measuring dataset quality, diversity, and downstream impact on model alignment and capability</li><li>
Create and manage both real-world and synthetic data pipelines</li><li>
Partner with lab research teams to translate their training objectives into concrete data and evaluation specifications</li></ul><p><b>
Tech stack:</b> Not specified</p><h2 class="jobSectionHeader"><b>
Requirements</b></h2><ul><li>
1&ndash;4 years of software engineering experience with strong technical depth</li><li>
Design targeted data slices that surface model failure modes across high-stakes domains (finance, code generation, enterprise workflows)</li><li>
Build and iterate on evaluation rubrics and reward signals powering RLHF and RLVR training pipelines</li><li>
Develop quantitative frameworks to measure dataset quality, diversity, and downstream impact on model alignment and capability</li><li>
Own end-to-end real world and synthetic data pipelines, from scoping with research teams to production-ready evaluation specs</li><li>
Run annotator modeling experiments to improve model capabilities across task types</li></ul><h2 class="jobSectionHeader"><b>
Green Flags</b></h2><ul><li>
Experience at RL environment companies</li><li>
Background in AI safety or benchmarking organizations like METR or Artificial Analysis</li><li>
Genuine obsession with how data structure, selection, and quality drive model behavior</li><li>
Ability to design lightweight experiments and move fast</li><li>
Former founders or early engineers at early stage startups</li><li>
Demonstrated ability to work hard, learn fast, and care deeply about details</li></ul><h2 class="jobSectionHeader"><b>
Red Flags</b></h2><ul><li>
Pure research profile with limited engineering output, this is a SWE role, shipping matters</li><li>
Looking for standard product engineering work &mdash; the real scope is data pipelines, reward modeling, and eval infra</li></ul><h2 class="jobSectionHeader"><b>
Why Join</b></h2><ul><li>
Outsized total cash: base plus substantial profit share, plus competitive equity</li><li>
Direct impact on frontier AI model development, working with the world's leading AI labs</li><li>
High ownership on a small, early team &mdash; scope, build, and ship end to end</li></ul><h2 class="jobSectionHeader"><b>
Details</b></h2><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site</li><li><b>
Compensation:</b> $180,000&ndash;$220,000 + equity</li><li><b>
Visa sponsorship:</b> O-1, OPT</li><li><b>
Employment type:</b> Full-time</li></ul></div>

Software Engineer, RL Environments

<div><p><b>San Francisco, CA &middot; On-site &middot; Full-time</b><br>
<b>Compensation:</b> $130,000&ndash;$150,000 base (up to $300K total cash comp) + equity</p><h3 class="jobSectionHeader"><b>
About the Company</b></h3><p>
A fast-growing, venture-backed AI company building the training data and evaluation infrastructure that leading frontier AI labs use to improve their models &mdash; designing high-signal datasets and running rigorous evaluations that go beyond static benchmarks. One of the fastest-growing companies in its cohort.</p><p>
Founded 2025 &middot; 11&ndash;50 people &middot; Industry: AI training data &amp; model evaluation infrastructure</p><h3 class="jobSectionHeader"><b>
The Role</b></h3><p>
A founding-level role at the intersection of technical execution and strategic leadership. You'll own high-impact initiatives end-to-end &mdash; from requirements through delivery &mdash; managing teams of engineers, data scientists, and ML specialists while shipping production code yourself, and interfacing directly with research teams at leading AI labs.</p><p><b>
What you'll be doing</b></p><ul><li>
Own end-to-end technical initiatives: scoping requirements, building solutions, managing experts through delivery, and shipping code yourself when it unblocks the team.</li><li>
Design and build technical infrastructure and tooling for dataset generation, quality control, and delivery pipelines across multiple concurrent lab contracts.</li><li>
Manage and mentor teams of software engineers, data scientists, and ML specialists; set technical direction and hold the bar for execution velocity.</li><li>
Interface directly with research teams at leading AI labs to translate their needs into technical specs and ensure delivery meets their standards.</li><li>
Debug production issues live under pressure; rapidly context-switch between hands-on engineering, team leadership, and strategic problem-solving.</li><li>
Support the founding team on the highest-impact work &mdash; internal tooling, major contracts, and hiring.</li></ul><p><b>
Tech stack:</b> Python; data pipelines, APIs, ML/AI tooling</p><h3 class="jobSectionHeader"><b>
Requirements</b></h3><ul><li>
CS degree, engineering experience, or equivalent demonstrated ability to ship technical projects</li><li>
Manage teams of technical experts across software engineering, data science, and machine learning</li><li>
Build technical infrastructure and tooling for dataset generation, quality control, and delivery pipelines</li><li>
Drive technical and operational initiatives end-to-end: scoping requirements, building solutions, and managing technical experts</li><li>
Interface directly with engineering and research teams at leading AI labs</li><li>
Support founding team on high-priority technical projects and operational initiatives</li><li>
Proficiency in Python and production-quality code</li><li>
Experience with data pipelines, APIs, or ML/AI tooling</li><li>
Strong leadership experience and communication skills</li><li>
Ability to context-switch rapidly between technical and strategic work</li><li>
Intense work ethic, agency, and drive</li><li>
Competitive nature and track record of exceptional achievement</li><li>
Undergraduate degree from the U.S., Canada, or the U.K.</li></ul><h3 class="jobSectionHeader"><b>
Green Flags</b></h3><ul><li>
Background in software engineering, ML engineering, AI research, or computer science</li><li>
Experience at top tech company (FAANG, frontier AI lab) or quantitative trading firm</li><li>
Prior startup experience or founding experience</li><li>
Willingness to work long hours and weekends when projects demand it</li></ul><h3 class="jobSectionHeader"><b>
Red Flags</b></h3><ul><li>
Worked cushy tech jobs (FAANG PM, etc.) and may not be used to intense work environments.</li><li>
Struggles with ambiguity or lacks examples of owning large, complex projects.</li><li>
Only interested in remote work &mdash; role is strictly in-person.</li><li>
Can't articulate why they want to pivot into AI ops or join a startup now.</li><li>
No experience managing teams or unclear on motivating people toward execution.</li></ul><h3 class="jobSectionHeader"><b>
Why Join</b></h3><ul><li>
Direct access to the founding team on their highest-priority problems</li><li>
Exposure to leading frontier AI labs; work that powers major contracts</li><li>
Up to $300K total cash comp plus meaningful equity in a fast-scaling company</li></ul><h3 class="jobSectionHeader"><b>
Details</b></h3><ul><li><b>
Location:</b> San Francisco, CA</li><li><b>
Work policy:</b> On-site &mdash; strictly in-person</li><li><b>
Compensation:</b> $130,000&ndash;$150,000 base (up to $300K total cash comp) + equity</li><li><b>
Visa sponsorship:</b> None available</li><li><b>
Employment type:</b> Full-time</li></ul></div>

Strategic Projects Lead - Coding

Google

<div>Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.<br>
<br>
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:<br>
<ul><li>
Health, dental, vision, life, disability insurance</li><li>
Retirement Benefits: 401(k) with company match</li><li>
Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment</li><li>
Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
</li><li>Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks</li><li>
Baby Bonding Leave: 18 weeks</li><li>
Holidays: 13 paid days per year</li></ul><br>
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: <b>San Francisco, CA, USA; Mountain View, CA, USA; New York, NY, USA; Washington D.C., DC, USA</b>.<h3 class="jobSectionHeader"><b>
Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree or equivalent practical experience.<br>
</li>
<li>3 years of experience designing, scoping, executing, and delivering research and analysis projects.<br>
</li>
<li>Experience translating business problems into research questions and translating research findings and insights into marketing recommendations.<br>
</li>
<li>Experience managing qualitative, quantitative and measurement agencies.<br>
</li>
<li>Experience managing cross-functional or cross-team projects.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Experience using AI tooling to conduct or facilitate research and measurement.</li>
<li>Knowledge of Washington DC and the US political environment.</li>
<li>Knowledge of policy in international and multinational (e.g. EU) policymaking processes.</li>
<li>Demonstrated interest in AI and its impact on society.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2>
In order to build excellent products and tell great stories, we must first profoundly understand our audiences - what motivates them, why they think and behave the way they do, and what they think of our brands and products. The Consumer Apps Marketing Research and Insights team is at the heart of developing this understanding.<div><p>
As a Research Manager, you will be embedded within the Reputation Marketing team, and inform how Google builds its reputation with the priority audiences shaping the AI landscape (policymakers, scientists, voters, and more). In this role, you will utilize both traditional research methods and new AI tooling to help the Reputation team understand and respond to the changing AI landscape via sharp, insights-driven marketing and communications.</p><p>
Your primary focus will be partnering with the AI Responsibility team: conducting and synthesizing brand tracking, qualitative research, and real-time social analysis across a variety of core issue areas (science, health, government, economy, and more). Your role will be to identify the audiences that matter in shaping the narratives for each issue, understand how those narratives spread and solidify, and provide tactical recommendations for how the AI Responsibility team should react. Managing stakeholder relationships, staying informed on Marketing priorities, scoping syntheses/studies to support strategy discussions, and managing a measurement framework will be an integral part of your day-to-day work.</p><p>
As a secondary-priority, you will help manage the global policymaker sentiment tracker. Your key responsibilities include helping to improve the program&rsquo;s operations, synthesizing findings and connecting dots between other programs, and presenting findings to teams across Google.</p></div>
Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems-from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can-changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
<br>
<br>
US: $116000 - $167000 (USD) + 15% bonus target + equity + benefits<br>
<br>
Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Scope custom research from start to finish, including: designing an effective brief, managing Requests for Proposals (RFPs), onboarding research agencies, choosing a methodology, executing the study, and deploying insights and recommendations via compelling narratives in a variety of formats (decks, sites, emails, presentations, etc.).</li>
<li>Distill findings from a variety of sources into cohesive research narratives, ultimately delivering the underpinning insight that drives critical leadership decision-making.</li>
<li>Manage the global policymaker tracking program, synthesize insights from the research, and present to teams throughout Google.</li>
<li>Share research findings and insights via presentations in forums large and small, with everyone from junior to executive staff.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Research and Insights Manager, Marketing, Reputation and AI Responsibility

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