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Eventual
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Eventual: Harnessing AI to transform ideas into massively scalable, cloud-ready architectures11-50 Employees
  • B2B
  • Early Stage
    Startup in initial stages

Jobs at Eventual

Eventual, helps businesses leverage AI to automatically build, scale and operate modern event-driven architectures that solve complex business orchestration and coordination problems. Our approach significantly accelerates the journey from ideas to implementation by translating business requirements written in natural language into a best-practice architecture built with eventualCloud’s distributed systems primitives running on AWS. This brings at least a 10x increase in delivery velocity by enabling an instant feedback loop between business and engineering teams, reducing what typically takes weeks of effort down to minutes or hours. Eventual scales with your business needs by utilizing Infrastructure-as-Code (IaC) to deploy production-ready services that integrate directly into your tech stack and operate within your own data, security, and privacy boundaries.
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Engineering

Technical Lead, Multimodal Research

NewPosted 7 days ago

Technical Lead, Multimodal Research

  • Own modeling strategy across the platform rather than one customer’s taxonomy: which model families, representations, and training approaches we invest in, which get prototyped, and when to move off one.
  • Take approaches from prototype into production inference at corpus scale, working with the data...
Engineering

Software Engineer, Multimodal Backend Systems

NewPosted 4 weeks ago

Software Engineer, Multimodal Backend Systems

  • Real-Time Video Infrastructure
  • Build our Streaming Architecture: Design, build, and optimize real-time WebRTC media pipelines and custom signaling mechanisms to stream multi-camera video feeds from robots to our platform
Engineering

Software Engineer, Data Systems

NewPosted 4 weeks ago

Software Engineer, Data Systems

  • Multimodal Storage (Data Lake): built against modern columnar data lake formats (Apache Parquet, Apache Iceberg etc) optimized for high-dimensional video, lidar and sensor logs.
  • Query Engine: build powerful querying capabilities. Our multi-stage query systems are built on database fundamentals such as partitioning, indexing, query planning, embeddings/vector search for search and retrieval as well as LLMs/VLMs for perception-based query predicates.
Engineering

Research Engineer, Multimodal Data

NewPosted 4 months ago

Research Engineer, Multimodal Data

  • Own the visual understanding roadmap end-to-end: from picking the model family for a customer's taxonomy to landing it in production inference at corpus scale.
  • Train, fine-tune, and evaluate VLMs, VQA models, embedding models, and convolutional perception models against customer datasets and benchmarks.