Founding Software Engineer, Platform & Infrastructure - DeepFrame - at Infinimind

Cox Exponential • Palo Alto, CA

5d • Onsite

About The Position

DeepFrame, InfiniMind’s video intelligence platform, helps enterprise customers search and analyze existing video using evidence-backed answers, timestamped clips, and rulebook reviews. The platform includes internally developed video-understanding models, ingestion and indexing across visual, speech, on-screen text, and time, search, and agents. It is offered as SaaS, in a customer’s own AWS account, or on premises.

The Founding Software Engineer, Platform & Infrastructure will be the first engineer on the ground in the US, working with the US go-to-market lead and the core engineering and research team in Tokyo. The role is primarily focused on building the platform, including GPU inference and video-processing infrastructure, ingestion and indexing pipelines, search and serving, and performance and cost improvements, with some customer-facing technical work to support integrations and pilots. Customer needs should be implemented in the core product rather than as one-off forks.

The engineer works daily with the CTO on technical matters and with the CEO on business priorities, and reports to the CEO. The CTO owns architecture, technical direction, code review, and technical feasibility; the CEO decides customer commitments when commercial and technical priorities conflict. The role is based in the Bay Area, with in-person work in Palo Alto at least three days per week and occasional customer travel.

The first 90 days include bringing DeepFrame up in a test AWS environment, merging a first production change, measuring GPU and pipeline costs, owning an infrastructure improvement, preparing a US customer pilot environment, and becoming the technical owner of the first US pilot. The role will also ship at least one US-driven feature or connector into the core product.

Requirements

• At least 5 years building production infrastructure or backend platforms, with substantial distributed-systems experience.
• Strong Python skills and proficiency in a systems language such as Go, Rust, or C++.
• Production experience running and optimizing model inference or ML pipelines on cloud GPUs, using CUDA, TensorRT, Triton, or similar technologies; AWS is preferred.
• Experience with containers and Kubernetes.
• Experience moving and processing large amounts of data reliably and cost-effectively.
• Ability to explain technical tradeoffs to customer engineers in meetings.
• Authorized to work in the United States by the start date; visa sponsorship is not available.
• Based in the Bay Area, able to work in person in Palo Alto at least three days per week, and able to travel to customers occasionally.

Nice To Haves

• Video and media processing experience, including ffmpeg, codecs, GStreamer, NVIDIA DeepStream, or NVDEC.
• Search infrastructure experience with vector databases, retrieval, and ranking at scale.
• ML systems experience, including serving foundation models and evaluation pipelines.
• Enterprise deployment experience, including VPC or on-premises installations, SSO, and security reviews.
• Experience working with teams across time zones, especially in Japan.
• Working proficiency in Japanese.

Responsibilities

• Build and operate AWS GPU infrastructure for video understanding, including model serving, batching, scheduling, and cost management per video-hour.
• Scale ingestion and indexing pipelines for large video libraries, including decoding, transcoding, frame, audio, and on-screen text processing, and embeddings.
• Work on the search and retrieval layer and customer-facing integration APIs.
• Build connectors to customer video sources, including S3, media asset management systems, and camera exports, and deliver results through APIs and webhooks.
• Deploy the product for enterprise customers as SaaS, in single-tenant AWS accounts, or on premises; own reliability and observability.
• Join technical customer meetings with the GTM lead and translate customer needs into product requirements.
• Collaborate daily with the CTO and Tokyo engineering team on architecture, priorities, code review, and integrating US needs into the core product.
• Own technical delivery of the first US customer pilot, from data access through the first results review.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed