Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI.

Our product is open-source and used at enterprise scale

Our distributed data engine Daft is open-sourced and runs on 800k CPU cores daily. This is more compute than Frontier, the world's largest supercomputer!

Today's data tooling (Spark, Presto, Snowflake) was built for a world of tabular data analytics, but does not generalize to the needs of modern ML/AI such as multimodal data, heterogenous compute and user-defined Python algorithms.

Eventual and Daft bridge that gap, making ML/AI workloads easy to run alongside traditional tabular workloads.

We're growing - come grow with us!

We are well funded by investors such as YCombinator, Caffeinated Capital, Array.vc and top angels in the valley from Databricks, Meta and Lyft.

Our team has deep expertise in high performance computing, big data technologies, cloud infrastructure and machine learning. Our team members have previously worked in top technology companies such as AnyScale, Tesla and Lyft.

We are looking for exceptional individuals with a passion for technology and a strong sense of intellectual curiosity.

If that sounds like you, please reach out even if you don't see a specific role listed that matches your skillsets - we'd love to chat!

About Eventual

Every breakthrough AI application—from foundation models to AI agents to autonomous vehicles—requires processing massive amounts of images, video, and complex data. But here's the problem: today's data platforms (Databricks, Snowflake, etc) are built on top of tools made for spreadsheet-like business analytics and SQL queries, not petabytes of multimodal information. This forces teams to waste months building complex infrastructure instead of solving the problems that are core to their business.

Our cofounders started Eventual in 2022 out of frustration with this exact challenge. Our mission is simple: make querying any type of data—images, video, audio, text—as intuitive as working with tables, yet powerful enough to handle petabytes at production scale. Unlike traditional engines with hardcoded operations, we handle the chaos of real production: coordinating with dozens of external APIs, managing GPU clusters, and turning the 0.1% failure rate that kills traditional systems into reliable execution. Our open-source engine Daft already powers critical AI workloads at companies such as Anthropic, Amazon, Mobileye, TogetherAI, and CloudKitchens.

We've assembled a world-class team from Databricks, AnyScale, Tesla, and Lyft with deep expertise in high-performance computing and big data infrastructure. Backed with significant funding from YCombinator, Caffeinated Capital, Array.vc, and top angels from Databricks, Anthropic, Meta, and Lyft, we're building the generational technology that will enable entirely new classes of AI breakthroughs. We’re in the process of doubling our team, join us today!

Your Role

As Daft Eventual's founding Technical Product Marketing Manager, you'll architect our go-to-market strategy during a pivotal transition—taking our open source project commercial. You'll be one of our first marketing hires, shaping how we connect with developers, grow our community, and drive adoption.

You'll wear multiple hats as both community champion and GTM strategist—crafting technical content that excites developers, speaking at conferences, and working with enterprise prospects to showcase how Daft solves their challenges. You'll bridge our engineering innovations with the ML/AI developers who need them most.

If you're energized by growing both an open source community and commercial business simultaneously—and want to define how thousands of developers experience data processing in AI—this is your role.

Key Responsibilities

• Developing and executing the go-to-market strategy for Daft, growing adoption across engineers and researchers working on the cutting edge of ML/AI

• Keeping a pulse on the latest developments in ML/AI and data, crafting compelling content (blog posts, case studies, documentation) that demonstrates Daft's unique value propositions

• Building relationships with key community members, contributors, and enterprise users

• Working closely with engineering to bring the amazing technical capabilities we're building every day to life as content that resonates with our target users

• Establishing metrics to measure adoption, engagement, and community growth

• Evangelizing Daft at industry events, meetups, and conferences

• Collaborating with enterprise customers to develop success stories and testimonials

What We Look For

We are looking for a candidate with technical depth who can effectively communicate complex concepts to technical audiences.

Our ideal candidate has:

• 5 - 10 years of product marketing experience, preferably with developer tools, data platforms, or open source technologies

• Strong technical foundation that enables understanding data tools and ML/AI workloads

• Proven experience growing developer communities and driving adoption of technical products, especially at Series A to C startups

• Excellent written and verbal communication skills, with that special ability to explain complex technical concepts

• Data-driven approach to measuring and optimizing marketing initiatives

• Experience with content creation, including technical blogs, documentation, and thought leadership pieces

• Familiarity with open source development models and community building

Most importantly, we are looking for someone who works well in small, focused teams with fast iterations and lots of autonomy. If you are passionate about developer tools, intellectually curious about data technologies, and excited to build communities around transformative open source software, we want you on the team!

Perks & Benefits

• Hybrid work environment - 3x a week in office

• Competitive comp and startup equity

• Catered lunches and dinners for SF employees

• Commuter benefit

• Team building events & poker nights

• Health, vision, and dental coverage

• Flexible PTO

• Latest Apple equipment

• 401k plan with match!

Our stack is a mix of Python and Rust. We integrate closely with distributed systems such as Ray and storage engines such as Apache Iceberg and AWS S3.

Examples of domains that we work in include:

• Databases: Daft employs modern query planning and optimizations for efficient execution of distributed workloads
• Enterprise Big Data: Daft integrates with data lake technologies such as Apache Iceberg and Hive, with record-setting I/O throughputs to these storage formats
• Low-Level System Programming: The execution core of Daft is written in Rust for memory-efficient data processing