advisor - scientific data engineer Jobs in San Francisco

advisor - scientific data engineer

ai engineer, ai & data platforms (aidp) Jobs in San Francisco

ai engineer, ai & data platforms (aidp)

backend engineer, api Jobs in San Francisco

backend engineer, api

backend engineer, integrations Jobs in San Francisco

backend engineer, integrations

backend software engineer Jobs in San Francisco

backend software engineer

data infrastructure engineer

Figma

<div>
 Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma&rsquo;s platform helps teams bring ideas to life&mdash;whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!
 
 
 We are looking for an experienced Data Engineer to partner with our Data Science and Data Infrastructure teams to own and scale our data pipelines. You&rsquo;ll also work closely with stakeholders across business teams including sales, marketing, and finance to ensure that the data they need arrives promptly and reliably. You&rsquo;ll play an integral role in building the metrics and self-serve reporting capabilities to unlock Figma&rsquo;s next phase of growth.
 
 
 This is a great role for an individual who is passionate about working with data and data systems, and who loves solving problems. You&rsquo;ll have a good sense for when it makes sense to build fast, scrappy solutions to unblock a key stakeholder vs. when to push back or bring in an outside service. The ideal candidate will be a great communicator who can help coordinate across multiple internal and external teams and takes pride in building end-to-end projects.
 
 
 This is a full time role that can be held from one of our US hubs or remotely in the United States.
 
 
 
 What you'll do at Figma
 
 
 :
 
 
 
 <ul>
 <li>
 Own, build, and maintain scalable data pipelines that connect various cloud data sources.
 </li>
 <li>
 Develop a deep understanding of Figma&rsquo;s core data models and optimize data pipelines for scale.
 </li>
 <li>
 Partner with the Data Science and Data Infrastructure teams to build new foundational data sets that are trusted, well understood, and enable self-service.
 </li>
 <li>
 Work with a wide range of cross-functional stakeholders to derive requirements and architect shared datasets; ability to document, simplify and explain complex problems to different types of audiences.
 </li>
 <li>
 Establish best practices for the development of specialized data sets for analytics and modeling.
 
 
 </li>
 </ul>
 We'd love to hear from you if you have:
 
 
 <ul>
 <li>
 4+ years in a relevant field.
 </li>
 <li>
 Fluency with both SQL and Python.
 </li>
 <li>
 Familiarity with Snowflake, dbt, Dagster, and ETL/reverse ETL tools.
 </li>
 <li>
 Excellent judgment and creative problem solving skills.
 </li>
 <li>
 A self-starting mindset along with strong communication and collaboration skills.
 
 
 </li>
 </ul>
 While not required, it&rsquo;s an added plus if you also have:
 
 
 <ul>
 <li>
 Knowledge in data modeling methodologies to design and build robust data architectures for insightful analytics.
 </li>
 <li>
 Experience with business systems such as Salesforce, Customer IO, Stripe, NetSuite is a big plus.
 
 
 </li>
 </ul>
 At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you&rsquo;re excited about this role but your past experience doesn&rsquo;t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
 
 
 
 Pay Transparency Disclosure
 
 
 
 If based in Figma&rsquo;s San Francisco or New York hub offices, this role has the annual base salary range stated below.
 
 
 Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. The listed range is a guideline, and the range for this role may be modified. For roles that are available to be filled remotely, the pay range is localized according to employee work location by a factor of between 80% and 100% of range. Please discuss your specific work location with your recruiter for more information.
 
 
 Figma offers equity to employees, as well a competitive package of additional benefits, including health, dental &amp; vision, retirement with company contribution, parental leave &amp; reproductive or family planning support, mental health &amp; wellness benefits, generous PTO, company recharge days, a learning &amp; development stipend, a work from home stipend, and cell phone reimbursement. Figma also offers sales incentive pay for most sales roles and an annual bonus plan for eligible non-sales roles. Figma&rsquo;s compensation and benefits are subject to change and may be modified in the future.
 
 
 Annual Base Salary Range:
 
 
 $140,000&mdash;$348,000 USD
 
 
 At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status
 
 ,
 
 or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
 
 
 We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.
 
 
 Examples of accommodations include but are not limited to:
 
 
 <ul>
 <li>
 Holding interviews in an accessible location
 </li>
 <li>
 Enabling closed captioning on video conferencing
 </li>
 <li>
 Ensuring all written communication be compatible with screen readers
 </li>
 <li>
 Changing the mode or format of interviews
 
 
 </li>
 </ul>
 To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding.
 
 
 By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice.
</div>

Data Engineer

Anthropic

<div><div><h2 class="jobSectionHeader">About Anthropic</h2>

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.</div><div><h2 class="jobSectionHeader">
About the role</h2>

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.

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.

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.
<h2 class="jobSectionHeader">
Responsibilities</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">You may be a good fit if you</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">Strong candidates may also have experience with</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>
The annual compensation range for this role is listed below.

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.</div></div>
Annual Salary:
$320,000 - $405,000 USD</div></div><div><h2 class="jobSectionHeader">
Logistics</h2>

Minimum education: Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: 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.

Visa sponsorship: 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.

We encourage you to apply even if you do not believe you meet every single qualification. 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. 
 
Your safety matters to us. 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.
<h2 class="jobSectionHeader">
How we're different</h2>

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.

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.
<h2 class="jobSectionHeader">
Come work with us!</h2>

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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.</div></div>

Software Engineer, Research Data Platform

Hellyeah AI

AI Engineer - Learn Engine: Intelligence &amp; OptimizationLocation: San Francisco HQ; ShanghaiAddress: San Francisco, CaliforniaEmployment Type: Full timeLocation Type: HybridDepartment: EngineeringCompensation: San Francisco $200K - $1M + 0.5% - 3% equityBuild 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.Must Have- Has built recommendation, optimization, or decision systems where outputs improve future inputs.- Strong statistical reasoning and experimentation judgment under noisy real-world data.- Strong LLM orchestration or agent-system experience for reasoning over campaign context.- Can design optimization policies, scoring systems, or automated recommendation loops.- AI-first development workflow and ability to ship production systems quickly.Nice to Have- Ad-tech optimization patterns: bid management, budget allocation, ROAS optimization.- Reinforcement learning experience.- Hyperparameter optimization experience.- Model fine-tuning experience.- Experience building agent-driven automation where LLM agents take actions.- Background in growth engineering, performance marketing, or data science.- Experience with Mastra or similar agent orchestration framework.What You Will OwnOwn 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.Pay: $200,000.00 - $1,000,000.00 per yearWork Location: In person

AI Engineer - Learn Engine: Intelligence & Optimization

Airbyte

<div>Airbyte is the data and action layer for AI agents. We give agents fast, accurate, authenticated access to business data across hundreds of sources, so they can discover the entities that matter, reason over real-time context, and take action in the systems they read from, not just observe them.
We started as the open-source standard for data movement and proved the economics of data integration at scale: hundreds of connectors, thousands of companies, and, since 2020, have raised $181M from leading investors including Benchmark, Accel, Altimeter, Coatue, and Y Combinator. As our CEO Michel Tricot puts it, &quot;the last ten years were all about structured data. The future is all about context.&quot; We're now building that context infrastructure for production-grade agents on the same open foundation, as agents become the primary consumers of enterprise data.
Our mission is unchanged: make data available and actionable to everyone, everywhere. That everyone now includes AI agents.<h2 class="jobSectionHeader">
Engineering Hiring Sprint:</h2>
We're growing our engineering team and are accelerating hiring through a focused Engineering Hiring Sprint. Rather than stretching interviews over several weeks, we're bringing exceptional candidates through an expedited process and making hiring decisions quickly.
Interview process:<ul><li>
Apply</li><li>
Technical Take-Home (Java or Python)</li><li>
Hiring Manager Interview</li><li>
In-Person Onsite (the week of July 20)</li><li>
Hiring decision by the end of the week</li></ul>
We're hiring across multiple engineering teams, including:<ul><li>
Platform Engineers</li><li>
Database Engineers</li><li>
Site Reliability Engineers</li><li>
Extensibility API Engineers</li><li>
AI Agents Engineers</li><li>
Engineering Managers</li></ul>
If you enjoy solving complex technical problems, moving quickly, embracing AI, and taking ownership of your work, we'd love to meet you.<h2 class="jobSectionHeader">
The Role:</h2>
Airbyte is looking for an Engineering Manager, Platform to lead the team responsible for the infrastructure, tooling, and engineering systems that power Airbyte Cloud, Airbyte Flex, and Airbyte Agents.
As an Engineering Manager on the Platform team, you'll lead the engineers responsible for cloud infrastructure, deployment systems, CI/CD, observability, reliability, and the internal tooling that powers engineering velocity across the company. Your work directly shapes both how fast engineers ship and how customers experience Airbyte. This isn't a keep-the-lights-on role. You'll make real tradeoffs between engineering velocity, customer-facing reliability, and long-term architecture every week, and you'll help define how AI transforms the way we build and operate software.
This role combines people leadership, technical strategy, operational excellence, and platform thinking. You'll help define how engineering works at Airbyte - not just what we build.<div> 
</div><h2 class="jobSectionHeader">
What You&rsquo;ll Do:</h2><ul><li>
Lead, mentor, and grow a team of Platform Engineers, Fullstack Engineers, and SREs. Recruit engineers who understand that infrastructure decisions are product decisions.</li><li>
Own the reliability and operational health of Airbyte's production systems.</li><li>
Define the roadmap for Airbyte's platform: infrastructure, CI/CD, deployment automation, observability, internal tooling, and the product surfaces built on top of them.</li><li>
Invest in and drive adoption of AI-powered workflows for debugging, release validation, infrastructure management, and developer productivity, moving past experimentation into real operational leverage.</li><li>
Lead incident response, run blameless postmortems, and ensure systemic fixes follow every outage. Continuously reduce operational toil through automation.</li><li>
Build leverage: a week-long task this year should take ten minutes next year.</li></ul><div> 
</div><h2 class="jobSectionHeader">
Success Metrics:</h2><ul><li>
Engineers deploy with confidence and ship faster quarter over quarter.</li><li>
Platform reliability improves as measured by customer-facing SLAs, not just internal dashboards.</li><li>
Operational toil decreases through automation, not heroics.</li><li>
Incidents are detected faster, resolved faster, and the same failure doesn't happen twice.</li><li>
Your team is engaged, growing, and building careers they're proud of.</li></ul><div> 
</div><h2 class="jobSectionHeader">
What You&rsquo;ll Need:</h2><ul><li>
5+ years of software engineering experience, 2+ years managing engineering teams.</li><li>
Experience leading Platform Engineering, Infrastructure, SRE, or Developer Productivity organizations.</li><li>
Strong understanding of cloud infrastructure, CI/CD, observability, and distributed systems.</li><li>
Experience operating production systems at scale.</li><li>
You think about platform work in terms of customer impact, not just engineering elegance.</li><li>
You've navigated the tension between paying down tech debt and shipping product, and you can articulate how you made those calls.</li><li>
Excellent communication skills. You can translate platform strategy into language that product, design, and business leaders understand.</li><li>
You have an insatiable desire to ship.</li></ul><h2 class="jobSectionHeader">
Nice To Have:</h2><ul><li>
Experience with AI-assisted engineering workflows or agentic software development.</li><li>
Experience building internal developer platforms.</li><li>
Familiarity with Terraform, Helm, Kubernetes, GitHub Actions, and cloud-native infrastructure.</li><li>
Experience with data infrastructure, ETL/ELT, or large-scale distributed systems.</li><li>
Experience contributing to open-source engineering organizations.</li><li>
Familiarity with Airbyte, connector ecosystems, or developer tooling platforms.</li></ul><div> 
</div><h2 class="jobSectionHeader">
Why This Role Matters:</h2>
Platform Engineering is the force multiplier for every engineering team at Airbyte.
Your mission is to build the systems, tooling, and infrastructure that enable engineers to move faster while making our platform more reliable, secure, and scalable. Success means every deployment becomes safer, every incident becomes easier to resolve, every engineer becomes more productive, and AI becomes a natural part of how software is built.
The best platform teams are invisible&mdash;they make everyone else dramatically more effective. That's the team you'll build.<h2 class="jobSectionHeader">
Location:</h2><ul><li>
Onsite 4 days/week in San Francisco, CA</li></ul><h2 class="jobSectionHeader">
Why You'll Love Working at Airbyte:</h2>
At Airbyte, we believe great work happens when people feel supported, trusted, and empowered to grow. Our market-leading Total Rewards package is designed to help you thrive professionally and personally. Our benefits and perks include:<ul><li>
Flexible PTO with a culture that encourages at least 25 days off annually</li><li>
16 weeks fully paid parental leave for all parents</li><li>
Comprehensive medical, dental, and vision coverage for employees and dependents</li><li>
401(k) retirement plan</li><li>
Professional development budget, conference sponsorship, and book reimbursement</li><li>
Commuter benefits and monthly internet reimbursement</li><li>
Breakfast and lunch in our San Francisco office</li><li>
A collaborative, in-person culture focused on learning, growth, and impact</li></ul>
If you find this role exciting, we encourage you to apply even if you think you don&rsquo;t meet all of the requirements!
We are not accepting agency submissions or recruiting firm support for this role. Unsolicited resumes will not be considered.
Airbyte is an equal opportunity employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, national origin, ancestry, age, physical or mental disability, pregnancy, genetic information, sex, sexual orientation, gender identity or expression, marital status, familial status, domestic violence victim status, veteran or military status, or any other legally recognized protected basis under federal, state or local laws. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Airbyte is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. Please let us know if you need assistance or accommodations due to a disability.
Compensation Range: $217K - $282K</div>

Engineering Manager, Platform - Hiring Sprint

Ouster

<div><h2 class="jobSectionHeader">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!</h2><h2 class="jobSectionHeader">
Role Overview</h2>
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.
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.<h2 class="jobSectionHeader">
Key Responsibilities</h2><h3 class="jobSectionHeader">
Test Software Development &amp; Abstraction</h3><ul><li>
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).</li><li>
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.</li><li>
Maintain Code Quality: Write clean, readable, and type-hinted Python code. Actively participate in peer code reviews and maintain structured Git-based development workflows.</li></ul><h3 class="jobSectionHeader">
Data Pipelines &amp; Station Reliability</h3><ul><li>
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.</li><li>
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.</li><li>
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.</li></ul><h3 class="jobSectionHeader">
Automation &amp; Test Rigor</h3><ul><li>
Automate Test Sequences: Develop multi-instrument automated test workflows using concurrent or multi-threaded Python concepts to minimize station cycle times.</li><li>
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.</li></ul><h2 class="jobSectionHeader">
Required Skills &amp; Qualifications</h2><ul><li>
Education: Bachelor&rsquo;s degree in Computer Science, Computer Engineering, Software Engineering, or a related technical discipline with a strong programming foundation.</li><li>
Professional Experience: 3+ years of experience writing production-grade software (ideally Python) interacting with hardware or processing data streams.</li><li>
Strong Python Foundation: Solid proficiency in core Python, including a clear understanding of decorators, higher-order functions, custom exceptions, and context managers.</li><li>
Instrument Interfacing: Direct experience communicating with hardware instruments using standard protocols like SCPI, PyVISA, Serial (RS-232/485), TCP/IP sockets, or Modbus.</li><li>
DevOps &amp; Infrastructure: Solid day-to-day comfort operating in Linux/Unix environments, utilizing Git for version control, and working with Docker containers.</li><li>
Data Competency: Practical experience writing and optimizing SQL queries (e.g., PostgreSQL, SQLite, or MariaDB) to handle high-frequency logging.</li></ul><h2 class="jobSectionHeader">
Preferred Qualifications</h2><ul><li>
Familiarity with Test-Driven Development (TDD) or building software simulations/digital twins for hardware components.</li><li>
Basic understanding of optical components, cameras, laser safety, or computer vision libraries (OpenCV).</li><li>
Experience supporting manufacturing lines or hardware prototyping cycles in electronics, automotive, or robotics industries</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) 
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. 
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. 
</div>
IWpEMUKGY8</div>

Software Engineer - Test Systems & Automation

MetaVoice

<div>
 
 At MetaVoice, our goal is an
 
 AI for voice conversations that's as natural as talking to a person.
 
 
 
 
 
 
 Today's voice AI fails at real-world conversations. It&rsquo;s slow, turn-based like a walkie-talkie, breaks with interruptions, and doesn&rsquo;t understand emotion.
 
 
 
 
 
 Developers can't build compelling experiences and users disengage. This limits voice AI to simple receptionist tasks and basic customer support, blocking meaningful services (sales, therapy, coaching) where dialogue and emotional intelligence matter most. Scaling current tech does not work.
 
 
 
 
 
 We're building voice AI that's as natural as talking to a person. Our approach is a duplex speech-to-speech model that learns conversational behaviour directly from data.
 
 
 
 
 
 MetaVoice is founded by:
 
 <ul>
 <li>
 Sid, founding engineer at Wayve.ai ( $2.5B+ raised)
 </li>
 <li>
 Vatsal, co-created Alexa&rsquo;s first AI voice.
 </li>
 </ul>
 
 
 
 
 We&rsquo;re passionate about building products people truly love.
 
 
 
 
 
 
 The role
 
 
 
 This is a founding engineer role owning the ML data &amp; evaluation platform that model development runs on.
 
 
 
 
 
 
 Who we're looking for
 
 
 
 You&rsquo;ve worked on distributed ML infra and understand that model quality is often a data problem. You:
 
 <ul>
 <li>
 Have a track record of taking initiative and learning things quickly.
 </li>
 <li>
 Care deeply about the people using the systems you build, whether they're researchers, operators or customers
 </li>
 <li>
 Have built something yourself (startup, side project, etc) or worked in an early-stage startup
 </li>
 </ul>
 
 
 
 
 
 What you've done
 
 
 <ul>
 <li>
 Built distributed ML data pipelines to generate datasets for training and evaluation, including curation, sampling and slicing.
 </li>
 <li>
 Built and operated MLOps infrastructure to train, evaluate and serve ML models, including versioning, orchestration and observability.
 </li>
 <li>
 Built eval systems to measure model quality and catch regressions.
 </li>
 <li>
 Developed internal tools and workflows for researchers and operators to explore data and iterate fast.
 </li>
 </ul>
 
 Strong plus:
 
 <ul>
 <li>
 Designed data flywheels: automated data collection and model update loops.
 </li>
 <li>
 Designed evaluation frameworks: automated or human-in-the-loop
 </li>
 <li>
 Experience with speech, audio, or conversational datasets
 </li>
 </ul>
 
 
 
 
 
 What we offer
 
 
 <ul>
 <li>
 Change the world (when we succeed)
 </li>
 <li>
 Environment to do the best work of your life.
 </li>
 <li>
 Small, humble and talent dense team.
 </li>
 <li>
 Opportunity to make cutting-edge research work in real-world scenarios.
 </li>
 <li>
 Work with 100+ TBs of data and 10B+ parameter models.
 </li>
 </ul>
 
 
 
 
 
 Culture
 
 
 <ul>
 <li>
 We're an in-person team in San Francisco &amp; love working together. It helps us learn from one another and make decisions quickly.
 </li>
 <li>
 We ship fast &amp; obsess over making customers happy.
 </li>
 <li>
 We offer high autonomy, allowing everyone to do their best work.
 </li>
 </ul>
 
 
 
 
 
 Compensation &amp; Benefits
 
 
 <ul>
 <li>
 Significant equity as a founding team member.
 </li>
 <li>
 $180K-300K base.
 </li>
 <li>
 Immigration support, we are immigrants ourselves.
 </li>
 <li>
 Fully covered medical, dental, and vision insurance
 </li>
 </ul>
 
 
 
 
 
 Interview Process
 
 
 
 We move with speed, and aim to go from first interview to offer within a week.
 
 <ul>
 <li>
 
 Vibe check, 30 mins:
 
 chat with one of the founders about the mission, product and your background
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 Technical Interview: 30 mins
 
 </li>
 <li>
 
 Culture interview: 30 mins
 
 </li>
 <li>
 
 Onsite co-work:
 
 Spend half a day with us. We'll build and iterate on a problem together.
 </li>
 </ul>
 
 
</div>

ML Platform Engineer (Data & Evals)

HappyRobot

<div>
 
 About HappyRobot
 
 
 
 HappyRobot is the infrastructure for enterprises to build and orchestrate AI workforces. Our AI workers don't just communicate - they make decisions, take action, and run operations autonomously across voice, email, and enterprise systems. Born in Y Combinator (S23) and backed by a16z and Base10 with over $60M raised, we power critical operations for global enterprises worldwide.
 
 
 Our platform is battle-tested in the most demanding environments - where AI has real consequences. We started in logistics, built our own voice stack, models, and orchestration layer from the ground up, and are now bringing that infrastructure to every enterprise that runs the real economy. Learn more about our vision in our manifesto.
 
 
 
 About The Role
 
 
 
 At
 
 HappyRobot
 
 , Full Stack Engineers own meaningful parts of the product and infrastructure end-to-end.
 
 
 We&rsquo;re looking for builders who thrive in ambiguity, care deeply about craft, and want real ownership over what they create.
 
 
 What We&rsquo;re Looking For
 
 
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 <li>
 Strong generalist &mdash; you&rsquo;re excellent on either the front end or back end, and comfortable working across the stack
 </li>
 <li>
 Front-end expertise with TypeScript and Next.js, including performance, UX, and clean architecture
 </li>
 <li>
 Back-end experience with Go, building reliable, scalable systems
 </li>
 <li>
 Product-minded engineer who understands tradeoffs between speed, quality, and scale.
 
 
 </li>
 </ul>
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Build and own entire sections of the product, including major parts of the web application
 </li>
 <li>
 Design, implement, and ship features end-to-end &mdash; from UI to APIs to infrastructure
 </li>
 <li>
 Help optimize and scale our voice AI infrastructure, improving latency, reliability, and cost
 </li>
 <li>
 Collaborate closely with founders and teammates to shape product direction
 </li>
 <li>
 Ship to production frequently and iterate based on real user feedback
 
 
 </li>
 </ul>
 
 Why join us?
 
 
 
 <ul>
 <li>
 Opportunity to work at a high-growth AI startup, backed by top investors.
 </li>
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 Rapidly growing and backed by top investors including a16z, Y Combinator, and Base10.
 </li>
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 Ownership &amp; Autonomy - Take full ownership of projects and ship fast.
 </li>
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 Top-Tier Compensation - Competitive salary + equity in a high-growth startup.
 </li>
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 Comprehensive Benefits - Healthcare, dental, vision coverage.
 </li>
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 Work With the Best - Join a world-class team of engineers and builders.
 
 
 </li>
 </ul>
 
 Our Operating Principles
 
 
 
 
 
 Extreme Ownership
 
 
 
 
 We take full responsibility for our work, outcomes, and team success. No excuses, no blame-shifting &mdash; if something needs fixing, we own it and make it better. This means stepping up, even when it&rsquo;s not &ldquo;your job.&rdquo; If a ball is dropped, we pick it up. If a customer is unhappy, we fix it. If a process is broken, we redesign it. We don&rsquo;t wait for someone else to solve it &mdash; we lead with accountability and expect the same from those around us.
 
 
 
 
 Craftsmanship
 
 
 
 
 Putting care and intention into every task, striving for excellence, and taking deep ownership of the quality and outcome of your work. Craftsmanship means never settling for &ldquo;just fine.&rdquo; We sweat the details because details compound. Whether it&rsquo;s a product feature, an internal doc, or a sales call &mdash; we treat it as a reflection of our standards. We aim to deliver jaw-dropping customer experiences by being curious, meticulous, and proud of what we build &mdash; even when nobody&rsquo;s watching.
 
 
 
 
 We are &ldquo;majos&rdquo;
 
 
 
 
 Be friendly &amp; have fun with your coworkers. Always be genuine &amp; honest, but kind. &ldquo;Majo&rdquo; is our way of saying: be a good human. Be approachable, helpful, and warm. We&rsquo;re building something ambitious, and it&rsquo;s easier (and more fun) when we enjoy the ride together. We give feedback with kindness, challenge each other with respect, and celebrate wins together without ego.
 
 
 
 
 Urgency with Focus
 
 
 
 
 Create the highest impact in the shortest amount of time. Move fast, but in the right direction. We operate with speed because time is our most limited resource. But speed without focus is chaos. We prioritize ruthlessly, act decisively, and stay aligned. We aim for high leverage: the biggest results from the simplest, smartest actions. We&rsquo;re running a high-speed marathon &mdash; not a sprint with no strategy.
 
 
 
 
 Talent Density and Meritocracy
 
 
 
 
 Hire only people who can raise the average; &lsquo;exceptional performance is the passing grade.&rsquo; Ability trumps seniority. We believe the best teams are built on talent density &mdash; every hire should raise the bar. We reward contribution, not titles or tenure. We give ownership to those who earn it, and we all hold each other to a high standard. A-players want to work with other A-players &mdash; that&rsquo;s how we win.
 
 
 
 
 First-Principles Thinking
 
 
 
 
 Strip a problem to physics-level facts, ignore industry dogma, rebuild the solution from scratch. We don&rsquo;t copy-paste solutions. We go back to basics, ask why things are the way they are, and rebuild from the ground up if needed. This mindset pushes us to innovate, challenge stale assumptions, and move faster than incumbents. It&rsquo;s how we build what others think is impossible
 
 
 
 The personal data provided in your application and during the selection process will be processed by Happyrobot, Inc., acting as Data Controller.
 
 
 
 
 By sending us your CV, you consent to the processing of your personal data for the purpose of evaluating and selecting you as a candidate for the position. Your personal data will be treated confidentially and will only be used for the recruitment process of the selected job offer.
 
 
 
 
 In relation to the period of conservation of your personal data, these will be eliminated after three months of inactivity in compliance with the GDPR and legislation on the protection of personal data.
 
 
 
 
 If you wish to exercise your rights of access, rectification, deletion, portability or opposition in relation to your personal data, you can do so through security@happyrobot.ai subject to the GDPR.
 
 
 
 
 For more information, visit
 
 
 https://www.happyrobot.ai/privacy-policy
 
 
 
 
 By submitting your request, you confirm that you have read and understood this clause and that you agree to the processing of your personal data as described.
 
</div>

Software Engineer - Full-Stack

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