David AI

About our Engineering team At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world’s first audio data research company. We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models. About this role As a Senior Backend Engineer at David AI, you’ll work across product surfaces to design clean APIs, build scalable services, and keep our systems performant under the weight of terabytes of audio data. In this role, you will Design, build, and maintain production-grade backend services that power everything from data collection to customer-facing insights. Own the architecture and performance of distributed systems that ingest, transform, and serve audio data at scale. Define and evolve internal APIs and service boundaries to support a growing set of ML and product features. Build resilient, observable, and easy-to-debug systems with strong performance characteristics. Collaborate with product, operations, and ML teams to rapidly iterate on new ideas and ship fast. Your background looks like 3+ years backend development building scalable APIs and services. Proficient with RESTful APIs, service interfaces, and database design (PostgreSQL, MySQL). Strong understanding of distributed systems and service-oriented architecture. Extensive cloud infrastructure and infrastructure-as-code experience. Proficient in profiling, debugging, and optimizing backend systems. Experience launching systems from ground up in high-growth environments (preferred). Bonus points if you have Familiarity with event-driven architectures, async processing, or large-scale data pipelines. Familiarity with CI/CD pipelines and DevOps best practices. Built scalable data pipelines that have facilitated large-scale event-driven workflows across large volumes of audio or video data. Deployed ML models for inference in a production environment. Some technologies we work with Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.

About our Engineering team At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world’s first audio data research company. We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models. About this role As a Software Engineer, Machine Learning Infrastructure at David AI, you will build and scale the core infrastructure that powers our cutting-edge audio ML products. You’ll be leading the development of the systems that enable our researchers and engineers to train, deploy, and evaluate machine learning models efficiently. In this role, you will Design and maintain data pipelines for processing massive audio datasets, ensuring terabytes of data are managed, versioned, and fed into model training efficiently. Develop frameworks for training audio models on compute clusters, managing cloud resources, optimizing GPU utilization, and improving experiment reproducibility. Create robust infrastructure for deploying ML models to production, including APIs, microservices, model serving frameworks, and real-time performance monitoring. Apply software engineering best practices with monitoring, logging, and alerting to guarantee high availability and fault-tolerant production workloads. Translate research prototypes into production pipelines, working with ML engineers and data teams to support efficient data labeling and preparation. Evaluate and integrate new MLOps technologies and optimization techniques to enhance infrastructure velocity and reliability. Your background looks like 5+ years of backend engineering with 2+ years ML infrastructure experience. Hands-on experience scaling cloud infrastructure and large-scale data processing pipelines for ML model training and evaluation. Proficient with Docker, Kubernetes, and CI/CD pipelines. Proven ML model deployment and lifecycle management in production. Strong system design skills optimizing for scale and performance. Proficient in Python with deep Kubernetes experience. Bonus points if you have Experience with feature stores, experiment tracking (MLflow, Weights and Biases), or custom CI/CD pipelines. Familiarity with large-scale data ingestion and streaming systems (Spark, Kafka, Airflow). Proven ability to thrive in fast-moving startup environments. Some technologies we work with Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.

About our Engineering team At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world’s first audio data research company. We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models. About this role As a Staff Product Engineer at David AI, you’ll lead our Product Engineering team in building cutting-edge products that help our customers make sense of the audio data they’ll use to train their models, working closely with researchers to consistently iterate on how to best collect our data. In this role, you will Lead full-stack feature development and iterate rapidly to deliver innovations to our users daily. Build scalable systems processing terabytes of audio data and deriving actionable insights. Deploy and evaluate LLM- and DSP-based solutions to enhance customer data understanding. Drive research iteration and interface deployment for data collection with researchers and Operations. Mentor engineers and establish technical standards as the team scales. Stay current with cutting-edge frameworks across software engineering, data engineering, ML, and signal processing. Your background looks like 6+ years of product-focused full-stack engineering experience. Strong web development fundamentals with experience building rapid prototypes and scalable user solutions. Proven track record delivering engineering solutions that provide customer value. Experience in fast-paced environments with detail-oriented execution. Focus on building intuitive, highly polished production-grade user experiences. Track record of success in technical leadership or engineering management. AI/ML or audio experience is not required but willingness to learn is essential. Bonus points if you have Educational or professional experience with digital signal processing and a deep understanding of speech. Experience building and deploying ML models in a production environment. Led (managed or tech-led) engineering teams in high-growth environments. Some technologies we work with Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.

About our Data Operations team Our Data Operations team powers David AI's Data Factory, transforming raw audio into high-quality training datasets for leading AI labs. Our mandate is to spin up new data pipelines and run them at a massive scale. This means starting from a model capability we want a model to unlock, experimenting with different shapes of data and collection strategies, and validating them with researchers. Once an approach works, we industrialize it, building pipelines that can process audio with reliability, quality, and efficiency. We are relentless operators who thrive in ambiguity, equally comfortable prototyping novel workflows as we are managing large-scale production systems. About this role As a Data Product Operations Lead, you’ll help drive David AI’s Data Factory — designing and scaling the pipelines that turn raw audio into high-quality datasets for frontier AI labs. You’ll take ownership of data products from 0→1 prototypes through 1→N scale, working hands-on to build workflows, validate them with researchers, and run them reliably at production scale. In this role, you will Own end-to-end success of a data pipeline, from early experiments to scaling up production systems that generate high-quality audio data at high volumes. Design and run pipelines that process a high volume of audio data with reliability, quality, and efficiency. Work with researchers at leading AI labs to identify new model capabilities and turn them into concrete data workflows and project plans. Lead cross-functional workstreams across Ops, Product, and Engineering to build scalable “data factory” systems. Monitor and improve pipeline health, spotting and fixing issues in sourcing, quality, or process. Drive impact with metrics, using throughput, quality, and cost to prioritize and improve. Take full-stack accountability across operations, product, engineering, and customers, solving bottlenecks and ensuring delivery. Your background looks like 2–6 years in high-intensity environments (e.g. founder, strategy consulting, or venture-backed ops). Technical foundation in CS, Industrial Engineering, or similar; SQL required. Systems thinker who can spot leverage points and design for scale and durability. Strong product intuition, able to work with engineers and researchers to get to the right answer fast. High-execution operator: fast, detail-oriented, and uncompromising on quality. Collaborative and low-ego, willing to roll up your sleeves. Bonus points if you have A track record of extreme ownership, caring about outcomes over tasks. Experience in data, ML, or large-scale operations. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.

About our Data Operations team Our Data Operations team powers David AI's Data Factory, transforming raw audio into high-quality training datasets for leading AI labs. Our mandate is to spin up new data pipelines and run them at a massive scale. This means starting from a model capability we want a model to unlock, experimenting with different shapes of data and collection strategies, and validating them with researchers. Once an approach works, we industrialize it, building pipelines that can process audio with reliability, quality, and efficiency. We are relentless operators who thrive in ambiguity, equally comfortable prototyping novel workflows as we are managing large-scale production systems. About this role As General Manager of Data Operations, you will lead one of the most critical functions at David AI. You’ll own a major slice of our Data Factory: the engine that powers high-quality, scalable data production. You’ll lead the team responsible for building and scaling pipelines, from 0→1 experiments that unlock new model capabilities to 1→N industrialization that processes data reliably and efficiently. In this role, you will Build and lead a team of Data Product Operations Leads, to spin up and scale data pipelines, from early experiments to production systems that generate high-quality audio data at scale. Act as a thought partner to executive leadership on how we can evolve and scale delivery capabilities in service of customer needs. Continuously monitor and improve pipeline health, spotting issues in sourcing, quality, or process early and owning solutions end-to-end. Use metrics to drive decisions, tracking throughput, quality, and cost to guide prioritization and identify where to scale or invest next. Work with researchers at leading AI labs to identify new model capabilities and turn them into concrete data workflows and project plans. Partner with our internal research team to design and test new data shapes that unlock frontier model capabilities. Own outcomes across functions, designing systems, managing execution, unblocking bottlenecks, and ensuring delivery at both prototype and production scale. Your background looks like 5–10 years of experience in high-ownership roles (e.g., founder, GM, COO, or strategy/ops at a venture-backed startup). Prior experience scaling large-scale operational efforts at high-growth startups or fast-paced companies. Technical fluency with data and operations; SQL proficiency required. Prior experience designing and scaling systems, processes, and teams across different customer segments and product lines. A relentless operator with high standards, bias to action, and strong attention to detail. Comfortable with ambiguity and rapid pace; thrives in a “build while flying” environment. Low-ego, collaborative, and mission-driven, focused on team and company success. Bonus points if you have Experience in data, ML, or large-scale operations. Background in CS, industrial engineering, or similar. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.

About our Growth team Our Growth team powers David AI's contributor network, the foundation of our Data Factory. We scale our global community of contributors across diverse domains - including voice actors, linguists, transcribers, and specialized domain experts - to meet customer data needs. We run rapid experiments across channels like job ads, marketing, communities, agencies, universities, multilingual forums, referral programs, and gig platforms. We systematize what works, turning successful experiments into scalable playbooks that drive sustainable contributor growth. About this role As a Growth Operations Lead, you'll scale our contributor network that powers the Data Factory, you’ll blend data-driven experimentation with human-centered design to build systematic processes that create best in class experiences for different contributor profiles worldwide. In this role, you will Lead contributor acquisition strategies across multiple channels: run A/B tests, iterate based on user feedback, and create repeatable playbooks that scale what works. Design and implement incentive systems that attract, engage, and retain high-quality contributors. Partner with Product and Engineering to design, test, and launch seamless contributor experiences built for engagement and scale. Run growth experiments across channels and geographies, measure results, and iterate quickly. Create high-conversion onboarding experiences that improve contributor engagement from day one. Collaborate with Operations to build scalable screening workflows that identify, evaluate, and onboard only top-quality contributors. Analyze funnel metrics to pinpoint drop-offs, improve retention, and forecast scaling needs in partnership with Operations. Your background looks like 2-5 years of experience in growth, marketing, or operations roles at fast-scaling companies Proven track record of building and scaling contributor networks, user acquisition funnels, or community-driven programs. Scrappy execution mindset, comfortable testing unconventional channels, iterating quickly, and doing hands-on work to prove concepts. Capable of interpreting data to guide actions and enhance performance for key growth metrics and KPIs such as CAC, LTV, churn, and conversion rates. Bonus points if you have Experience driving fast-paced growth programs within user marketplaces. Ability to write your own SQL queries to extract actionable insights. Experience building and automating scalable workflows and proofs of concept using code or no-code tools to boost operational efficiency. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.

About our Engineering team At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world’s first audio data research company. We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models. About this role As Head of Engineering, you'll be the technical backbone for our engineering team, leading execution across product, infrastructure, and AI systems. Partnering closely with the CTO, you'll co-develop the long-term technical vision and architecture, then translate it into a clear roadmap and operating cadence. You'll ensure delivery quality and nurture a collaborative, high-velocity engineering culture. This is a strategic role with broad autonomy where you'll shape how we build from day one. In this role, you will Lead the design and development of core tools that help users make sense of audio data for model training, working closely with researchers to continually improve how we collect data. Hire, structure, and mentor the engineering team while setting and upholding high performance standards. Oversee the delivery of full-stack features that thousands of users interact with daily. Build scalable data processing pipelines to extract actionable insights from terabytes of audio data every day. Rapidly iterate on research hypotheses in partnership with the Head of Research and Head of Operations - deploying interfaces to collect new data efficiently. Your background looks like 3+ years of engineering management experience. Experience leading technical organizations through rapid growth phases at high-growth startups or scale-ups. Strong background in distributed systems, real-time data processing, or machine learning infrastructure. A high degree of comfort digging into systems with deep technology stacks. A passion for problem solving and providing technical leadership to peers. Bonus points if you Are a former founder. Some technologies we work with Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.

About our Machine Learning team Our Machine Learning team sits at the intersection of cutting-edge research and production systems, transforming raw audio into high-signal data for leading AI labs and enterprises. We own the full ML lifecycle - from researching novel speech processing algorithms to deploying models processing terabytes of audio daily. About this role As an Applied ML Engineer at David AI you'll build cutting-edge speech and audio models, production inference systems and resilient pipelines that showcase what high-quality data can really do. In this role, you will Research, design, and implement solutions using advanced signal processing. algorithms and bleeding edge ML models with application to speech and audio. Develop production-grade inference algorithms, pipelines, and APIs with cross-functional teams that unlock key insights into our data for our customers. Collaborating with our Operations team to gather useful training and evaluation datasets to improve the quality of our models. Architect systems that enable resilient, durable inference and evaluations. Your background looks like 5+ years of professional audio ML experience, including DSP and ML audio algorithm development. End-to-end ownership of ML pipelines, from proof-of-concept to production deployment. Strong coding skills in Python and proficiency with deep learning frameworks such as PyTorch. Ability to translate research papers and ideas into high-quality, production-ready code. Experience deploying ML systems for production inference with cloud technologies. Track record of setting ML roadmaps, influencing technical direction, and prioritizing research and infrastructure investments. Ability to assess model quality in the context of user experience and business value. Bonus points if you have PhD or Masters in Computer Science or a related field. Experience training generative AI models. Expertise in audio signal processing both classical and machine learning techniques. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.

About our Engineering team At David AI, our engineers build the pipelines, platforms, and models that transform raw audio into high-signal data for leading AI labs and enterprises. We're a tight-knit team of product engineers, infrastructure specialists, and machine learning experts focused on building the world’s first audio data research company. We move fast, own our work end-to-end, and ship to production daily. Our team designs real-time pipelines handling terabytes of speech data and deploys cutting-edge generative audio models. About this role As a Product Engineer at David AI, you'll build cutting-edge tools that help our users make sense of the audio data they'll use to train their models, working closely with researchers to consistently iterate on how to best collect our data. In this role, you will Ship full-stack features that thousands of users will interact with daily. Build scalable systems to create core data processing pipelines that derive actionable insights from terabytes of audio data every day. Build, deploy, and evaluate LLM and DSP based solutions to increase our customers’ understanding of nuanced features across our datasets. Iterate rapidly on our research hypotheses by working closely with researchers and our Operations team to deploy interfaces to collect new data. Stay up-to-date with cutting edge technologies and frameworks to apply to our current product offering across software engineering, data engineering, machine learning, and signal processing. Your background looks like 2+ years of product-focused full-stack engineering experience. Strong full-stack web development fundamentals with experience in creating rapid prototypes, as well as building solutions that scaled to many users. A proven track record of delivering engineering solutions that contributed value to customers. Experience working in a high-pace environment that constant progress was enabled by detail-oriented execution. Emphasis on building intuitive products and experiences that resonates with users and has built highly polished production-grade products. AI/ML or audio experience is not required but you should be excited to learn. Bonus points if you have Educational or professional experience with digital signal processing and a deep understanding of speech. Experience building and deploying ML models in a production environment. Led (managed or tech-led) engineering teams in high-growth environments. Some technologies we work with Next.js, TypeScript, TailwindCSS, Node.js, tRPC, PostgreSQL, AWS, Trigger.dev, WebRTC, FFmpeg. Compensation and benefits Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry. Competitive salary and equity package. Flexible PTO policy. Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. Paid lunch and dinner in the office, every day through DoorDash. 401k access.