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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

Ouster

<div><h2 class="jobSectionHeader"><b>At Ouster, we build sensors and tools for engineers, roboticists, and researchers, so they can make the world safer and more efficient. We've transformed LIDAR from an analog device with thousands of components to an elegant digital device powered by one chip-scale laser array and one CMOS sensor. The result is a full range of high-resolution LIDAR sensors that deliver superior imaging at a dramatically lower price. Our advanced sensor hardware and vision algorithms are used in autonomous cars, robotics, industrial, and smart infrastructure applications (among many others). If you&rsquo;re motivated by solving big problems, we&rsquo;re hiring key roles across the company and need your help!</b></h2><h2 class="jobSectionHeader"><b>
Role Overview</b></h2><p>
Ouster is seeking a Software Engineer to build, optimize, and maintain our automated production test infrastructure. In this role, you will move beyond basic, linear automation scripting to develop clean, decoupled, and reusable software interfaces that connect our Lidar optical and electrical hardware to our data systems.</p><p>
We treat manufacturing test infrastructure with the same algorithmic rigor and software standards as core product code. If you are a strong software developer who loves seeing your code interact with physical devices, optimize factory-floor data pipelines, and drive software quality metrics, this role is for you.</p><h2 class="jobSectionHeader"><b>
Key Responsibilities</b></h2><h3 class="jobSectionHeader"><b>
Test Software Development &amp; Abstraction</b></h3><ul><li><p>
Develop Hardware Abstraction Layers: Implement and scale Python-based software wrappers to cleanly separate test sequence logic from lower-level instrument drivers (e.g., power supplies, digital multimeters, spectrometers).</p></li><li><p>
Apply Modular Design: Utilize modern software design patterns (e.g., Factory, Strategy, Wrapper) to ensure test code remains flexible, future-proofed, and easy to maintain as instrumentation evolves.</p></li><li><p>
Maintain Code Quality: Write clean, readable, and type-hinted Python code. Actively participate in peer code reviews and maintain structured Git-based development workflows.</p></li></ul><h3 class="jobSectionHeader"><b>
Data Pipelines &amp; Station Reliability</b></h3><ul><li><p>
Optimize Data Flow: Implement and debug high-volume data pipelines that package and stream local parametric test data securely into centralized manufacturing databases and execution systems.</p></li><li><p>
Build Fault-Tolerant Code: Write defensive software routines, including intelligent retry logic, exception handling, and local data buffering to prevent station downtime during intermittent network or server disruptions.</p></li><li><p>
Triage &amp; Troubleshooting: Analyze test station execution logs to systematically diagnose whether a failure on the line stems from a software bug, instrument communication dropout, or a genuine product defect.</p></li></ul><h3 class="jobSectionHeader"><b>
Automation &amp; Test Rigor</b></h3><ul><li><p>
Automate Test Sequences: Develop multi-instrument automated test workflows using concurrent or multi-threaded Python concepts to minimize station cycle times.</p></li><li><p>
Software Validation: Write unit tests and implement software mocking frameworks to validate the stability of your test code before deploying updates to a live production line.</p></li></ul><h2 class="jobSectionHeader"><b>
Required Skills &amp; Qualifications</b></h2><ul><li><p>
Education: Bachelor&rsquo;s degree in Computer Science, Computer Engineering, Software Engineering, or a related technical discipline with a strong programming foundation.</p></li><li><p>
Professional Experience: 3+ years of experience writing production-grade software (ideally Python) interacting with hardware or processing data streams.</p></li><li><p>
Strong Python Foundation: Solid proficiency in core Python, including a clear understanding of decorators, higher-order functions, custom exceptions, and context managers.</p></li><li><p>
Instrument Interfacing: Direct experience communicating with hardware instruments using standard protocols like SCPI, PyVISA, Serial (RS-232/485), TCP/IP sockets, or Modbus.</p></li><li><p>
DevOps &amp; Infrastructure: Solid day-to-day comfort operating in Linux/Unix environments, utilizing Git for version control, and working with Docker containers.</p></li><li><p>
Data Competency: Practical experience writing and optimizing SQL queries (e.g., PostgreSQL, SQLite, or MariaDB) to handle high-frequency logging.</p></li></ul><h2 class="jobSectionHeader"><b>
Preferred Qualifications</b></h2><ul><li><p>
Familiarity with Test-Driven Development (TDD) or building software simulations/digital twins for hardware components.</p></li><li><p>
Basic understanding of optical components, cameras, laser safety, or computer vision libraries (OpenCV).</p></li><li><p>
Experience supporting manufacturing lines or hardware prototyping cycles in electronics, automotive, or robotics industries</p></li></ul><div>
The base pay will be dependent on your skills, work experience, location, and qualifications. This role may also be eligible for equity &amp; benefits. ($107,000 - $150,000)<p><br>
We acknowledge the confidence gap at Ouster. You do not need to meet all of these requirements to be the ideal candidate for this role.</p><p><br>
Ouster is an Equal Employment Opportunity employer that pursues and hires a diverse workforce. Ouster does not make employment decisions on the basis of race, color, religion, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military status, or any other basis protected by local, state, or federal laws. Ouster also strives for a healthy and safe workplace, and prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance, Ouster considers qualified applicants with arrest and conviction records for employment. If you have a disability or special need that requires accommodation, please let us know.</p><br>
</div><p>
</p><p>IWpEMUKGY8</p></div>

Software Engineer - Test Systems & Automation

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

Wells Fargo

<div><p><b>About this role:</b></p><p>
Wells Fargo is seeking a Principal Engineer to join our AI Platforms and Enterprise Execution Group as part of Consumer Technology. Learn more about the career areas and business divisions at wellsfargojobs.com.</p><p></p><p>
This role focuses on designing and delivering enterprise‑scale strategic initiatives in reusable AI patterns that deliver business and customer value.</p><p></p><p>
This is a hands‑on Principal Engineer role for a technical leader who designs, builds, and scales AI‑driven platforms, while operating at enterprise scope. The Principal Engineer serves as a technical authority who codes, prototypes, and reviews architecture, not just oversees execution</p><p><b><br>
In this role, you will:</b></p><ul><li>
Act as a trusted advisor to leadership, guiding the development and influence of applications, networks, information security, databases, operating systems, web technologies, and emerging AI capabilities to address highly complex business and technical needs across multiple groups</li><li>
Lead the strategy and resolution of highly complex, unique challenges through end‑to‑end solution design, including Generative and Agentic AI systems, cloud‑native platforms, and legacy modernization efforts that require long‑term vision, creativity, innovation, and advanced analytical thinking</li><li>
Translate advanced technology expertise, deep understanding of enterprise business objectives, organizational structure, and the broader technology ecosystem into scalable engineering solutions, such as reusable architectures, AI-enabled platforms, and production‑ready systems</li><li>
Provide vision, direction, and technical leadership to senior leaders on implementing innovative business solutions, embedding AI and automation into product delivery workflows, decision support, and developer productivity while ensuring alignment with security, compliance, and responsible AI standards</li><li>
Maintain deep awareness of industry best practices, emerging technologies, and AI advancements, proactively recommending innovations that modernize operations, improve efficiency and quality, and create competitive advantage for the organization</li><li>
Strategically engage with professionals and managers at all levels of the enterprise, serving as an expert technical advisor and escalation point for complex platform, data, and AI decisions while mobilizing and guiding large‑scale, cross‑organizational initiatives and communicating progress to executive leadership</li></ul><p></p><p><b><br>
Required Qualifications:</b></p><ul><li>
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education</li><li>
7+ years of senior engineering experience, including architecture and hands‑on delivery of large‑scale platforms and systems</li><li>
4+ years of experience developing or deploying AI‑powered tools, chatbots, LLM‑based automation, or agentic workflows, including understanding of AI risks, observability needs, and stakeholder communication</li><li>
3+ years of hands‑on experience across Cloud architectures including Google Cloud Platform, Microsoft Azure, AWS, etc. and internal platforms such as Tachyon</li><li>
3+ years of experience operating at both keyboard‑level technical depth and executive‑level technical storytelling</li></ul><p></p><p><b>
Desired Qualifications:</b></p><ul><li>
Experience working within agile product operating models in large enterprise environments, including agile software delivery and cloud infrastructure</li><li>
Financial services experience preferred; Business Banking domain experience is beneficial but not required</li><li>
Demonstrated ability to mentor senior and staff engineers, raising the technical bar of the organization</li><li>
Proven strategic thinking, analytical problem‑solving, and sound technical judgment in fast‑paced settings</li><li>
Proven experience with cloud infrastructure and containerization, including enterprise compute, storage, and IaaS environments</li><li>
Demonstrated curiosity and innovation mindset for advancing Generative and Agentic AI solutions within regulated enterprise contexts</li><li>
Strong organizational savvy and customer centricity, with the ability to navigate complex enterprise structures and align technology to business outcomes</li></ul><p><b><br>
Job Expectations:</b></p><ul><li>
Ability to travel as needed
</li><li>This position offers a hybrid work schedule</li><li>
This position is not eligible for Visa sponsorship</li></ul><p></p><p><b>
Job Location</b>:</p><p>
333 Market St - San Francisco, California 94105</p><p>
300 S. Brevard - Charlotte, North Carolina 28202</p><p>
2600 S Price Rd - Chandler, Arizona 85286</p><p></p><p><b>
Pay Range</b></p><p><br>
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.</p>
$159,000.00 - $305,000.00<p></p><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p><b>
Benefits
</b></p><p></p><p>Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.</p><ul><li>
Health benefits</li><li>
401(k) Plan</li><li>
Paid time off</li><li>
Disability benefits</li><li>
Life insurance, critical illness insurance, and accident insurance</li><li>
Parental leave</li><li>
Critical caregiving leave</li><li>
Discounts and savings</li><li>
Commuter benefits</li><li>
Tuition reimbursement</li><li>
Scholarships for dependent children</li><li>
Adoption reimbursement</li></ul></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p><p><b>
Posting End Date:</b></p><p></p>
12 Jul 2026<ul><li><b><i>Job posting may come down early due to volume of applicants.</i></b></li></ul><p></p><p><b>
We Value Equal Opportunity</b></p><p></p><p>
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.</p><p></p><p>
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit&rsquo;s risk appetite and all risk and compliance program requirements.</p><p></p><p><b>
Applicants with Disabilities</b></p><p></p><p>
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.</p><p></p><p><b>
Drug and Alcohol Policy</b></p><p></p><p><br>
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.</p><p></p><p><b>
Wells Fargo Recruitment and Hiring Requirements:</b></p><p></p><p>
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.</p><p>
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.</p></div><p></p>

Principal AI Engineer

Ontrac Solutions

<div><h1 class="jobSectionHeader"><b>Overview</b></h1>
<p>We are seeking a Principal GenAI Architect / Forward Deployed Principal Engineer to lead the design, delivery, and productionization of enterprise-grade Generative AI solutions within a highly regulated banking environment. This role will partner directly with business, product, engineering, architecture, risk, cyber, legal, compliance, and model governance teams to translate high-impact financial services use cases into scalable, secure, and compliant AI systems.</p>
<p>The ideal candidate has deep experience designing and delivering production-scale GenAI solutions across enterprise environments, with strong exposure to banking, financial services, risk management, customer operations, regulatory controls, and data protection requirements. This person will serve as a recognized GenAI expert across the organization, helping define reusable patterns, influence platform roadmaps, and raise the technical bar for responsible AI adoption across lines of business.</p>
<h2 class="jobSectionHeader"><b>Key Responsibilities</b></h2>
<h3 class="jobSectionHeader"><b>GenAI Architecture &amp; Production Readiness</b></h3>
<p>Own and define enterprise-grade GenAI architectures for banking and financial services use cases, including RAG pipelines, agentic workflows, prompt orchestration, and multi-model routing strategies.</p>
<p>Drive production readiness for GenAI solutions, ensuring scalability, resiliency, observability, latency optimization, security, and cost efficiency.</p>
<p>Lead complex architectural decisions across data ingestion, vector databases, model selection, guardrails, API scalability, performance optimization, and secure integration with banking systems.</p>
<p>Establish reference architectures, reusable patterns, and best practices to accelerate responsible GenAI adoption across lines of business.</p>
<p>Partner with central AI platform teams to align solution architecture with enterprise AI services, platform capabilities, banking technology standards, and long-term roadmap priorities.</p>
<h3 class="jobSectionHeader"><b>Banking Use-Case Delivery</b></h3>
<p>Act as a Forward Deployed Principal Engineer, partnering directly with business, product, and engineering teams to deliver high-impact GenAI use cases from ideation through production.</p>
<p>Translate banking and financial services business problems into clear AI system designs, technical requirements, and non-functional requirements with measurable outcomes.</p>
<p>Support GenAI use cases across areas such as customer service, operations, knowledge management, risk, compliance, fraud, employee productivity, document intelligence, and internal workflow automation.</p>
<p>Troubleshoot and resolve complex issues across non-production and production environments.</p>
<p>Partner closely with application teams to ensure AI solutions integrate effectively into existing banking platforms, enterprise workflows, data environments, APIs, and control frameworks.</p>
<p>Influence platform roadmap by feeding real-world banking use-case requirements back into central AI services and enterprise AI platform teams.</p>
<h3 class="jobSectionHeader"><b>Governance, Risk &amp; Compliance</b></h3>
<p>Ensure all AI solutions align with banking risk, cyber, model governance, data protection, privacy, and regulatory expectations.</p>
<p>Partner with Cyber, Model Risk Management, Legal, Compliance, Risk, and Data Governance teams to design compliant AI patterns without slowing delivery.</p>
<p>Embed security, privacy, responsible AI, ethical AI, explainability, human oversight, and auditability into solution design by default.</p>
<p>Help define practical implementation patterns that balance innovation, speed, governance, regulatory expectations, and enterprise control requirements.</p>
<p>Ensure GenAI solutions are designed with appropriate guardrails for sensitive financial data, customer information, personally identifiable information, and regulated business processes.</p>
<h3 class="jobSectionHeader"><b>Organizational Influence &amp; Mentorship</b></h3>
<p>Serve as a recognized GenAI expert across the enterprise, regularly consulted by engineering, architecture, product, risk, compliance, and leadership teams.</p>
<p>Mentor senior and staff-level engineers and help raise the technical bar across banking technology teams.</p>
<p>Contribute to internal communities of practice, architecture reviews, executive-level technical discussions, AI governance forums, and knowledge-sharing sessions.</p>
<p>Represent enterprise GenAI capabilities in internal innovation forums, banking technology discussions, and responsible AI showcases.</p>
<h2 class="jobSectionHeader"><b>Required Qualifications</b></h2>
<p>7+ years of software engineering experience, with significant depth in AI/ML, data-intensive systems, distributed systems, or enterprise-scale platforms.</p>
<p>2+ years of hands-on Python programming experience.</p>
<p>2+ years of experience designing and delivering production-scale Generative AI systems in an enterprise environment.</p>
<p>2+ years of experience with LLMs, prompt engineering, and RAG architecture.</p>
<p>2+ years of experience with vector databases, semantic search, and retrieval systems.</p>
<p>2+ years of experience with API-driven, cloud-native architectures.</p>
<p>2+ years of experience with distributed systems, performance optimization, scalability, and reliability engineering.</p>
<p>Experience working within banking, financial services, fintech, or another highly regulated enterprise environment.</p>
<h2 class="jobSectionHeader"><b>Preferred Qualifications</b></h2>
<p>Strong understanding of banking technology environments and non-functional requirements, including security, scalability, resiliency, observability, latency, auditability, and cost management.</p>
<p>Demonstrated Principal-level impact, with influence across multiple teams, platforms, business units, or lines of business.</p>
<p>Experience operating in highly regulated environments, with financial services or banking experience strongly preferred.</p>
<p>Hands-on experience with agentic AI frameworks, AI workflow orchestration, and multi-model routing.</p>
<p>Prior experience in a Forward Deployed Engineer, embedded engineering, or business-facing technical delivery model.</p>
<p>Experience partnering with risk, cyber, legal, compliance, data governance, or model governance teams to deliver production AI solutions.</p>
<p>Familiarity with banking controls, customer data protection, model risk management, audit requirements, regulatory expectations, and responsible AI principles.</p>
<p>Ability to communicate complex technical concepts clearly to senior executives, technical stakeholders, risk partners, compliance teams, and non-technical business leaders.</p>
<h2 class="jobSectionHeader"><b>Ideal Candidate Profile</b></h2>
<p>The ideal candidate is a hands-on Principal-level engineer and architect who can move seamlessly between strategy, architecture, and execution in a banking environment. They are comfortable working directly with business teams to understand real-world financial services problems, while also going deep with engineering teams on system design, performance, security, governance, and production readiness.</p>
<p>This person brings strong technical judgment, enterprise banking delivery experience, and the ability to build practical, compliant GenAI solutions that can scale responsibly across a large financial institution.</p></div>

Resourceful Talent Group

<div><p><b>Compensation:</b> $185,000 to $260,000 base + meaningful early-stage equity</p><p></p><p><b>
About the Role</b></p><p>
We are hiring a <b>Founding Product Engineer</b> for our client, a well-funded, fast-growing AI startup that is transforming how professional services firms operate through intelligent automation.</p><p></p><p>
With strong customer traction, paying clients already using the product, and an ambitious roadmap ahead, they&rsquo;re looking for an exceptional engineer who wants to help build a category-defining product from the ground up. This is a rare opportunity to work directly with the founding team, take ownership of core product development, and play a key role in shaping both the product and the engineering culture.</p><p></p><p><b>
What You&rsquo;ll Do</b></p><ul><li>
Build and ship product features across the full stack, from concept to production</li><li>
Design scalable frontend and backend solutions using modern web technologies</li><li>
Develop integrations with third-party platforms and APIs</li><li>
Build AI-powered features using LLMs and agent-based workflows</li><li>
Collaborate closely with the founders on product strategy, technical decisions, and roadmap planning</li><li>
Move quickly, solve complex problems, and continuously improve the product based on customer feedback</li></ul><ul><li>
2 to 7 years of professional software engineering experience</li><li>
Strong experience with TypeScript, React, Next.js, Node.js, and SQL or PostgreSQL</li><li>
Experience building and shipping production-ready full-stack applications</li><li>
Hands-on experience working with LLMs, AI tools, or agentic systems</li><li>
Ability to take ownership and thrive in a fast-paced startup environment</li><li>
Strong product mindset and passion for building user-focused software</li><li>
Excellent communication and problem-solving skills</li></ul><p></p><p><b>
Nice to Have</b></p><ul><li>
Experience working at a seed or Series A startup</li><li>
Experience building API integrations or workflow automation tools</li><li>
Exposure to AI-first products or automation platforms</li><li>
Previous experience as an early engineering hire or working directly with founders</li></ul><p></p><p><b>
Why Join?</b></p><ul><li>
Competitive base salary of <b>$185K to $260K</b></li><li>
Meaningful early-stage equity</li><li>
Opportunity to become one of the first engineering hires</li><li>
Work directly with experienced founders who have successfully built and scaled startups</li><li>
Join a company with proven market demand and paying customers</li><li>
Hybrid schedule in San Francisco (3 days in office)</li><li>
Relocation assistance available</li><li>
Visa transfer support for qualified candidates</li><li>
High-impact role with significant ownership and opportunities for growth</li></ul></div><p></p>

Founding Product Engineer

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

Explore 51+ Automation engineer in San Francisco this July. Find roles across top companies and apply now to boost your career.

51 automation engineer jobs In San Francisco

AI Engineer - Learn Engine: Intelligence & Optimization

Software Engineer - Test Systems & Automation

Founding Engineer - Applied AI

Principal AI Engineer

Principal AI Engineer

Founding Product Engineer

Machine Learning Engineer