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data infrastructure engineer

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we&rsquo;re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain &mdash; and we&rsquo;re looking for talented people who want to help. 
 
You&rsquo;ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You&rsquo;ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you&rsquo;ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. 
 
Amazon Interactive Video Service (Amazon IVS) is AWS's fully managed live streaming service, built on the same battle-tested technology that powers Twitch and trusted by thousands of enterprises across gaming, social, live commerce, sports, and entertainment.
 
 
Our mission: enable developers to build communities around live video. We handle everything from ingest to processing to delivery at global scale, so developers can focus on creating interactive, engaging live experiences for their audiences. Whether you're streaming to tens of millions of concurrent viewers or just getting started, Amazon IVS removes the complexity so developers can move fast. 
 
As a Data Infrastructure Engineer, you will be responsible for empowering internal teams and IVS customers with the data they need to make key operational and business decisions. We operate petabyte-scale data infrastructure for collecting, processing, and warehousing IVS data. We support streaming and batch pipelines to facilitate analytics, reporting, and ML workloads. We offer analytics tools and data products designed to make it easy and fast for our customers to extract the insights they need from their data. 
 
Key job responsibilities 
<ul><li>Design, implement, and maintain scalable data infrastructure in native AWS</li><li>Build and optimize data pipelines (batch and streaming) to support analytics, reporting, and ML workloads</li><li>Ensure data quality, reliability, and observability through monitoring, logging, and automated alerting</li><li>Work closely with product and analytics teams to understand requirements and deliver high-performance solutions</li><li>Champion best practices for security, compliance, and governance in data infrastructure</li><li>Identify opportunities to optimize performance and cost of data platforms</li><li>Stay current with emerging tools, frameworks, and cloud services in the data infrastructure ecosystem</li></ul> 
A day in the life 
Your primary focus will be empowering customers to succeed with their data by ensuring they can: 
<ul><li>Gather and access data at scale &ndash; Enable seamless data collection and retrieval that grows with their needs</li><li>Extract meaningful insights &ndash; Provide the right tools and capabilities to uncover the answers they're seeking</li><li>Trust their data &ndash; Maintain confidence in the completeness, accuracy, and reliability of their information</li></ul>
Achieving these goals requires close collaboration and strong partnerships with Product and Data Science teams to deliver solutions that truly meet customer needs.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>5+ years of non-internship professional software development experience</li><li>5+ years of programming with at least one software programming language experience</li><li>5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Experience as a mentor, tech lead or leading an engineering team</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li><li>Experience in software development, or experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 193,300.00 - 261,500.00 USD annually 
USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually</div>

Sr. Data Infrastructure Engineer, Amazon Interactive Video Service (IVS)

Mento

<div><h3 class="jobSectionHeader">About Mento</h3>

Mento is a career technology company that helps people be exceptional and thrive at work through human, AI, and software-based coaching. We're on a mission to provide people access to the best support, advice, and mentorship at work and empower them to take action on it. In a world where jobs and careers are rapidly changing, we believe that transformational growth and continuous improvement is mandatory for people and companies to thrive. We are on a mission to bring our unique model of coaching to every member of the global workforce.

We strive to create a fun, conscientious, collaborative, and supportive work environment. We are a US-based, remote-first company, backed by leading VCs and angel investors.
<h3 class="jobSectionHeader">
About The Role</h3>

We're looking for our first Data Engineer to build the data infrastructure that powers insights and features across our coaching platform. You'll own data pipelines for coaching sessions, user analytics, and business operations, while establishing the foundation for our data architecture.

This is not purely about business analytics - In this role, you'll join our engineering team and work closely with product, engineering, coaching, and leadership teams. You'll be embedded in product development&mdash;understanding feature requirements, instrumenting data collection, and building systems that power product capabilities.
<h3 class="jobSectionHeader">
Key Responsibilities:</h3>

Build data pipelines for coaching and user analytics. You'll create pipelines that process coaching session data, user interactions, and AI-generated outputs. These pipelines will power everything from product analytics to coaching effectiveness metrics to business intelligence dashboards.

Build data systems that power product features. You'll create data pipelines that feed back into the product&mdash;user progress tracking, coaching insights, customer dashboards, and more. You'll work with product and engineering to understand what data products need and build reliable systems to deliver it.

Establish our data infrastructure and architecture. As our first data engineer, you'll make key decisions about our data stack&mdash;choosing and implementing tools for orchestration, transformation, warehousing, and analytics. You'll build foundations that can scale with the company.

Process and analyze AI/LLM outputs. You'll work with data from our AI coaching systems, building pipelines to analyze LLM responses, track coaching quality, and generate insights about how users interact with AI coaches.

Support business operations and analytics. You'll build data systems that track customer success metrics, billing data, user engagement, and operational KPIs. Your work will directly inform business decisions and product strategy.

Create accessible analytics infrastructure. You'll build systems that make data available to non-technical stakeholders through dashboards, reports, and self-service analytics tools. You'll think about data quality, documentation, and usability.

Work closely with product on instrumentation and data collection. You'll collaborate with product and engineering teams to instrument new features, define events and metrics, and ensure we're collecting the right data. You'll be involved in product discussions and understand feature requirements from a data perspective.
<h3 class="jobSectionHeader">
Who We're Looking For</h3>

We're looking for a data engineer with mid to senior-level experience who can work independently, make architectural decisions, and build data systems from the ground up. 

You have strong data engineering fundamentals. You're experienced with SQL, Python, and building data pipelines. You understand data modeling, ETL/ELT patterns, and how to design scalable data architectures. You've worked with databases like PostgreSQL and have opinions on data infrastructure tools.

Bonus: You're comfortable with Go. Our backend stack is Ruby and Go, with new development preferentially in Go. While we are happy to use Python as the primary language for data work, comfort with Go is a plus for building production data services and working closely with the backend team.

You can drive technical decisions about data infrastructure. You've evaluated and implemented data tools before&mdash;whether orchestration frameworks, warehouses, transformation tools, or BI platforms. You can assess our needs and recommend the right stack for an early-stage company.

You're comfortable working with diverse data sources. You'll work with operational databases, event streams (Redis), document stores (Elasticsearch), API data, and LLM outputs. You can navigate different data formats and build reliable integrations.

You're comfortable working closely with product teams. You've worked embedded with product and engineering, participated in product discussions, and built data systems that directly power product features. You understand the difference between building for analysis versus building for production product use.

You can build both analytical and operational data pipelines. You've built pipelines for analytics and business intelligence, but you've also built systems that feed data back into products in real-time or near-real-time. You understand the different requirements and tradeoffs.

You have some experience with AI/ML data. You've worked with LLM outputs, unstructured data, or analytics for AI-powered products. You understand the unique challenges of working with AI-generated content and can design appropriate data models.

You work well independently in an early-stage environment. You're comfortable with ambiguity and can prioritize work without extensive direction. You can balance building for immediate needs while creating foundations for future scale.
<h3 class="jobSectionHeader">
Why Work with Us?</h3>

We are a company dedicated to empowering professionals to live meaningful careers. That starts with our culture at Mento.

You're excited about building data infrastructure that serves multiple purposes&mdash;analytics, business intelligence, and powering product features. You want to work closely with product teams and see your data systems directly impact user experience.

We work hard to foster a workplace built around trust, respect, and collaboration. As a remote-first company, we believe in flexibility and autonomy&mdash;as long as you're delivering great work and staying connected with your teammates, you can work from anywhere.

This is an opportunity to join an early-stage, mission-driven team as the founding data engineer. You'll have significant ownership over our data architecture and direct impact on both product and business strategy.

We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users. If you're passionate about building data systems that help people thrive at work, we want to hear from you. 


Other benefits and perks include:

✈️ Fully Remote - ability to work from anywhere with bi-annual team offsites

 Competitive salary and equity

 Medical, dental, vision, and a 401k plan

 Unlimited vacation (We actually mean this! it's important to keep yourself fresh)

 $500 home office stipend

 Access to your own Mento Coach</div>

Data Engineer

Middesk

<div>About Middesk
Middesk makes it easier for businesses to work together. Since 2018, we&rsquo;ve been transforming business identity verification, replacing slow, manual processes with seamless access to complete, up-to-date data. Our platform helps companies across industries confidently verify business identities, onboard customers faster, and reduce risk at every stage of the customer lifecycle.
Middesk came out of Y Combinator, is backed by Sequoia Capital and Accel Partners, and was recently named to Forbes Fintech 50 List and cited as an industry leader in business verification by digital identity strategy firm, Liminal.
About Middesk Engineering:
Middesk is, at its core, a data company. We live by the quality of our data assets and the engine that powers them. We&rsquo;re on a mission to build a comprehensive and complete business dataset for every business in the world. As part of the Data Platform team at Middesk, you&rsquo;ll collaborate with Data Science, Infrastructure and Product Engineering teams to build and maintain our own proprietary Entity Resolution system used to power the Middesk business identity platform, scaling our system to resolve millions of business identities across hundreds of data sources and thousands of distinct data sets. You&rsquo;ll often work with and support product engineers looking to launch new products and features.
The Role:
We're looking for a senior engineer to own and drive the technical direction of our data platform. You'll design data infrastructure systems that operate reliably at scale, define the architecture for how we acquire, transform, and serve data to product teams, and partner closely with engineering leadership to align platform strategy with company priorities.
You'll be expected to independently scope complex projects from ambiguous problem statements, break them into incremental deliverables, and drive them to completion while keeping stakeholders informed and adapting when priorities shift. You'll also play a key role in elevating the engineering practices of the team through mentorship, code review, and setting technical standards.
What You'll Do:<ul><li>
Own platform architecture and technical direction for how we ingest, transform, and serve data across highly variable input formats - business entity data sourced from thousands of government agencies, registries, and third-party providers, each with its own schema, cadence, and reliability profile</li><li>
Design and build systems for scale - both the infrastructure we need today and the infrastructure we'll need at 2&ndash;5x our current volume</li><li>
Scope and drive complex projects end-to-end, breaking ambiguous problems into well-defined milestones with clear deliverables and timelines</li><li>
Design AI-powered tooling to improve how we acquire and maintain data using LLMs, AI agents, and agent orchestration</li><li>
Partner with product engineering, data science, and business teams to understand data needs and translate them into platform capabilities</li><li>
Establish and maintain data governance and quality standards across the platform, ensuring the integrity and reliability of the data our customers depend on for compliance and risk decisions</li></ul>
What We&rsquo;re Looking For:<ul><li>
7+ years of professional software engineering experience, with meaningful time spent on data infrastructure, data engineering, or backend platform work (targeting Senior to Staff Level Engineers)</li><li>
Experience designing and operating systems at meaningful scale, ideally within a larger or rapidly scaling engineering organization</li><li>
Track record of independently owning and delivering complex, multi-milestone projects - from scoping through launch</li><li>
Strong data modeling instincts and deep familiarity with SQL, pipeline orchestration (Airflow, Dagster, etc.), and data transformation patterns</li><li>
Experience with distributed data processing frameworks (Spark, Flink, Beam, or similar) and an understanding of when and how to apply parallelization to scale pipelines beyond single-node limits</li><li>
Proficiency in one or more of: Python, Ruby, JavaScript/TypeScript, Java</li></ul>
Nice to Haves:<ul><li>
Experience working with or building AI/LLM-powered tooling or data products (strongly preferred)</li><li>
Experience with scraper technologies, including agentic AI</li><li>
Experience building and designing collections stored on Elasticsearch</li><li>
Experience operating event-driven data pipelines using serverless compute (e.g., AWS Lambda, Google Cloud Functions, Azure Functions) and managed cloud services</li><li>
Experience with Terraform, Datadog, or Kubernetes</li></ul>
Compensation Range: $205K - $275K</div>

Software Engineer, Data Platform

OpenAI

<div>
 
 About The Team
 
 
 
 The Applied team works across research, engineering, product, and design to bring OpenAI&rsquo;s technology to consumers and businesses.
 
 
 We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.
 
 
 
 About The Role
 
 
 
 We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI!
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse.
 </li>
 <li>
 Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.
 </li>
 <li>
 Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions.
 </li>
 <li>
 Implement robust and fault-tolerant systems for data ingestion and processing.
 </li>
 <li>
 Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear.
 </li>
 <li>
 Ensure the security, integrity, and compliance of data according to industry and company standards.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You
 
 
 
 <ul>
 <li>
 Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering).
 </li>
 <li>
 Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
 </li>
 <li>
 Experience with distributed processing technologies and frameworks, such as Hadoop, Flink and distributed storage systems (e.g., HDFS, S3).
 </li>
 <li>
 Expertise with any of ETL schedulers such as Airflow, Dagster, Prefect or similar frameworks.
 </li>
 <li>
 Solid understanding of Spark and ability to write, debug and optimize Spark code.
 
 
 </li>
 </ul>
 This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees.
 
 
 
 About OpenAI
 
 
 
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
 
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
 
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 
 
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
 
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 
 
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 
 
 OpenAI Global Applicant Privacy Policy
 
 
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
 
 Compensation Range: $230K - $385K
</div>

Data Engineer, Analytics

DoorDash

<div><h1 class="jobSectionHeader">About the Team</h1>

Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash.
<h1 class="jobSectionHeader">
About the Role</h1>

DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. This is a hybrid position in San Francisco, CA; Sunnyvale, CA; or Seattle, WA. 

<h1 class="jobSectionHeader">
You're excited about this opportunity because you will&hellip;</h1>
<ul><li>Work with business partners and stakeholders to understand data requirements</li>
<li>Work with engineering, product teams and 3rd parties to collect required data</li>
<li>Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse</li>
<li>Develop and implement data quality checks, conduct QA and implement monitoring routines</li>
<li>Improve the reliability and scalability of our ETL processes</li>
<li>Manage a portfolio of data products that deliver high-quality, trustworthy data</li>
<li>Help onboard and support other engineers as they join the team</li>
</ul><h1 class="jobSectionHeader">We're excited about you because&hellip;</h1>
<ul><li>5+ years of professional experience</li>
<li>3+ years experience working in data engineering, business intelligence, or a similar role</li>
<li>Proficiency in programming languages such as Python/Java</li>
<li>3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP</li>
<li>Expert in Database fundamentals, SQL and distributed computing</li>
<li>3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink.</li>
<li>Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms</li>
<li>Excellent communication skills and experience working with technical and non-technical teams</li>
<li>Knowledge of reporting tools such as Tableau, Superset and Looker</li>
<li>Comfortable working in fast paced environment, self starter and self organizing</li>
<li>Ability to think strategically, analyze and interpret market and consumer information</li>
<li>You must be located near one of our engineering hubs indicated above
</li></ul>We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on August 21, 2023.

Please see the independent bias audit report covering our use of Covey here.<div><h2 class="jobSectionHeader">
About DoorDash</h2>

At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users&mdash;from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order food to a company that people turn to for any and all goods. 
 
DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees' happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.
<h2 class="jobSectionHeader">
Our Commitment to Diversity and Inclusion</h2>

We're committed to growing and empowering a more inclusive community within our company, industry, and cities. That's why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.

Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on &quot;protected categories,&quot; we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce &ndash; people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.

Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.

If you need any accommodations, please inform your recruiting contact upon initial connection.</div></div>

Senior Software Engineer, Data Engineering

Domu

<div>
 At Domu.ai, we're building the infrastructure that will replace call centers at the world's largest financial institutions. Voice AI that handles thousands of live calls every day for Fortune 500 banks and insurers, end-to-end. Call volume is 3x-ing monthly. We're hitting problems most startups never see: real-time voice AI at scale, legacy banking infrastructure, enterprise telephony, and regulatory constraints.
 
 
 The role
 
 
 \ As the
 
 Software Engineer
 
 you'll.....
 
 
 <ul>
 <li>
 Build and own core product features: Backend systems, APIs, voice infrastructure, wherever the product needs you. Code ships daily and goes live for Fortune 500 clients.
 </li>
 <li>
 Work on things most engineers never touch: telephony systems, real-time voice processing, and integrations with legacy financial infrastructure. The problems are hard. That's the point.
 </li>
 <li>
 95%+ of your time will be coding and building.
 </li>
 <li>
 We're looking for engineers who can own one of these areas: the orchestration layer that coordinates our voice AI systems, infrastructure scaling and low-level performance, security as a generalist building for Fortune 500 financial institutions, or product engineering close to users finding high-leverage wins.
 </li>
 <li>
 Know what it feels like when things are working: real customers, real revenue, a product people actually need. You also know the chaos, the pace, the things that break at the worst possible time. You've seen both sides and you want to do it again with a team that's already found traction.
 
 
 </li>
 </ul>
 How we work
 
 
 <ul>
 <li>
 Four engineers. Everyone ships to production.
 </li>
 <li>
 We do dailies. We groom tickets. But we keep process light and in service of the work, not the other way around. We'd rather spend time building than talking about building.
 </li>
 <li>
 We care about doing great work. Not just shipping, but shipping something you're proud of. Clean abstractions. Systems that don't page you at 3am. Code you wouldn't be embarrassed to open-source. We build things that last because we're the ones maintaining them.
 </li>
 <li>
 Ownership here is real. You won't be handed tasks from a backlog. You'll see what needs to happen and do it. That's how a small team ships to Fortune 500 customers.
 </li>
 <li>
 We hire people whose judgment we trust, then get out of their way. No passengers.
 
 
 </li>
 </ul>
 What you bring
 
 
 <ul>
 <li>
 3+ years of experience as a software engineer
 </li>
 <li>
 Previously worked at a Series A (or similar stage) startup and went through the same hypergrowth challenges Domu is facing
 </li>
 <li>
 Experience dealing with legacy systems and refactoring them into sustainable, scalable architectures
 </li>
 <li>
 Strong backend fundamentals - can own features end-to-end from design to production
 </li>
 <li>
 Proficiency in TypeScript and/or Python
 </li>
 <li>
 Cares about doing great work - clean abstractions, reliable systems, code you'd be proud to open-source
 
 
 </li>
 </ul>
 Extras we'd be excited about
 
 
 <ul>
 <li>
 Telephony/Voice infrastructure - SIP, SRTP, WebRTC, or platforms like Telnyx, Twilio, LiveKit
 </li>
 <li>
 High-throughput distributed systems - queue workers, event-driven architectures, handling 1M+ daily transactions
 </li>
 <li>
 PostgreSQL at scale - query optimization, replication, connection pooling
 </li>
 <li>
 Kubernetes - production deployments, scaling stateful services
 </li>
 <li>
 Real-time data pipelines - ClickHouse, Kafka, or similar OLAP/streaming solutions
 </li>
 <li>
 AWS infrastructure - SQS, containerized deployments
 </li>
 <li>
 Compliance-conscious environments - SOC 2, ISO 27001, or fintech/enterprise security requirements
 </li>
 <li>
 Experience with AI/ML integrations in production (LLMs, voice AI)
 </li>
 <li>
 Familiarity with contact center / dialer systems
 </li>
 <li>
 You've been through the early stages of a startup before.
 </li>
 <li>
 You care about the craft. You want to build something good, not just something that works.
 
 
 </li>
 </ul>
 Why Domu
 
 
 <ul>
 <li>
 You'll be engineer #5. Small team, high leverage. Your work ships immediately.
 </li>
 <li>
 Real traction. Post-revenue, Fortune 500 customers, 3x monthly growth. This isn't a bet on an idea. The product works and customers are paying for it.
 </li>
 <li>
 You'll learn how enterprise deals work from an engineering seat. You'll see the direct line between your code and revenue.
 </li>
 <li>
 Early enough to shape the product, the team, and the culture.
 
 
 </li>
 </ul>
 What we offer
 
 
 <ul>
 <li>
 Healthcare
 </li>
 <li>
 weekly stipend for food and transportation
 </li>
 <li>
 gym membership
 </li>
 <li>
 equipment budget (strict rules on noisy mechanical keyboards)
 </li>
 <li>
 whatever tools you need
 </li>
 </ul>
</div>

Software Engineer

Hayden AI

<div>
 
 About Us
 
 
 
 At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
 
 
 From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
 
 
 
 Job Title:
 
 Machine Learning Operations Engineer
 
 
 
 Company:
 
 Hayden AI Technologies, Inc.
 
 
 
 Location:
 
 460 Bryant Street, Suite 100, San Francisco, CA 94107
 
 
 
 Position Duties
 
 
 
 <ul>
 <li>
 Optimize orchestration processes to ensure efficient deployment and management of AI models.
 </li>
 <li>
 Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance.
 </li>
 <li>
 Upgrade throughput to enhance scalability and responsiveness of AI systems.
 </li>
 <li>
 Collaborate with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency.
 </li>
 <li>
 Ship new features and updates rapidly while maintaining high levels of quality and reliability.
 </li>
 <li>
 Deploy and monitor machine learning models produced by deep learning engineers.
 </li>
 <li>
 Design, deploy, and maintain performant and scalable processes for data acquisition and manipulation to enhance dataset accessibility.
 </li>
 <li>
 Participate actively in the team's software development process, including design reviews, code reviews, and brainstorming sessions.
 </li>
 <li>
 Maintain accurate and updated software development documentation.
 
 
 </li>
 </ul>
 
 Degree Requirements
 
 
 
 Bachelor of Science or Engineering degree or a foreign equivalent in Robotics, Machine Learning, Computer Science, Electrical Engineering, Electronics and Telecommunication Engineering, or a related field.
 
 
 
 Experience Requirement
 
 
 
 One (1) year of work experience in the job offered or as a Deep Learning Engineer, Perception Engineer II, MLOps, Research Engineer II, Machine Learning, Computer Vision Intern, or another related deep learning engineer role.
 
 
 
 Other Special Requirements
 
 
 
 <ul>
 <li>
 One (1) year of work experience with all of the following:
 </li>
 <ul>
 <li>
 Deploying real-world applied computer vision (including deep learning models) on edge devices
 </li>
 <li>
 Python programming and software design
 </li>
 <li>
 C++
 </li>
 <li>
 Software development tools and libraries including PyTorch, OpenCV, TensorFlow, MLflow
 </li>
 <li>
 Automated data annotation
 </li>
 <li>
 Distributed training in the cloud
 </li>
 <li>
 Deploying and managing GPU clusters for ML pipelines and workflows
 
 </li>
 </ul>
 </ul>
 
 Rate of Pay:
 
 $135,699.00 to $190,000.00 per year
 
 
 
 Location of Position and Interview:
 
 
 
 Hayden AI Technologies, Inc.
 
 
 460 Bryant Street, Suite 100
 
 
 San Francisco, CA 94107
 
 
 
 Applicants Should Submit Resumes To
 
 
 
 Janet Le-Mcintosh
 
 
 janet.le@hayden.ai
 
 
 Hayden AI Technologies, Inc.
 
 
 460 Bryant Street, Suite 100
 
 
 San Francisco, CA 94107
</div>

Machine Learning Operations Engineer

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