Mid/Senior AI Cinematic Video Editor (Full Remote - Argentina)
The Mid/Senior AI Cinematic Video Editor is responsible for conceptualizing scripts based on current production needs centered around existing AI characters, creating narrative-driven longform video content including stylized and explicit NSFW visuals with a focus on storytelling, atmosphere, and visual coherence. They own and manage end-to-end AI video production workflows from ideation, prompting, generation, editing, post-production, and final delivery. This includes working extensively with ComfyUI pipelines to build, customize, and optimize node-based workflows for image and video generation. They utilize tools such as Stable Diffusion (AUTOMATIC1111), ComfyUI, Runway, and other AI video platforms to produce high-quality visual sequences, ensure consistent character appearance, style, and scene continuity across longer narratives using advanced techniques, integrate motion graphic design and color correction for cohesive final outputs, experiment rapidly with new AI models, tools, and techniques and share skills with the team, align with the Content Lead's creative direction while maintaining autonomy in execution and technical decisions, and continuously refine workflows for efficiency, scalability, and output quality.
Optical Engineer - Freelance AI Trainer
Design original optics problems that simulate real physics research workflows; ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); develop problems requiring non-trivial reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics; base problems on real research challenges or practical applications from optics and physics practice; document problem statements clearly and provide verified correct answers.
Software Engineer (Brazil)
Design, develop, test, deploy, maintain, and improve scalable, secure, and high-performance backend systems with a focus on high availability, low latency, and cost-effectiveness. Act as the subject matter expert in infrastructure when designing new products and introducing new technology to existing products. Collaborate closely with engineering and research teams to integrate infrastructure components with product features to optimize system performance and user experience. Design event-driven architectures and develop APIs and microservices for real-time processing and analytics. Ensure system reliability, performance, and scalability through monitoring, logging, and error handling. Stay current with emerging trends, technologies, and methodologies to enhance infrastructure capabilities. Participate in code reviews, contribute to open-source projects, and mentor junior engineers.
Full Stack AI Engineer (.NET)
Develop and maintain full stack applications using modern frontend frameworks (React or similar) and .NET-based backend services. Build and integrate AI-powered features such as automation, summarization, and recommendations into existing workflows. Design and consume REST APIs and support backend services in .NET. Collaborate with cross-functional teams to identify opportunities for automation and AI-driven improvements. Work with structured and unstructured data to support AI/ML use cases. Contribute to improving system performance, scalability, and reliability. Support basic monitoring and troubleshooting of production systems.
Expansion Account Executive (Boston)
Debug and fix issues in the Arize platform and ship pull requests with fixes. Build internal tools and copilots powered by generative AI to enhance the team. Rapidly prototype proof-of-concepts for customer use cases. Collaborate across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.
Technical Product Marketing Manager
Debug and fix issues in the platform and ship PRs with the fixes. Build internal tools and copilots powered by generative AI to enhance the team. Rapidly prototype proof-of-concepts for customer use cases. Work across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.
Ascendancy - Full-Stack Engineer
The Fullstack Engineer is responsible for owning and building product features end-to-end, including scoping, architecture, implementation, testing, and deployment. They work across the stack using Python, Next.js, and TypeScript to develop high-quality, user-facing applications with a strong focus on performance, security, and clean design. The role includes collaborating closely with product and design teams, contributing to AI-driven features such as LLM workflows and agents, and shaping both the user experience and underlying systems, including authentication and database design.
DevSecOps Engineer (TypeScript & Agentic AI)
Debug and fix issues in the platform and ship pull requests with those fixes. Build internal tools and copilots powered by generative AI to enhance the team’s capabilities. Rapidly prototype proof-of-concepts for customer use cases. Work collaboratively across Engineering, Product, and Solutions teams to unblock customers and advance AI adoption.
Span - Sr Product Engineer
Work on projects such as developing a product that root causes KTLO work and recommends solutions, building a software catalog that works for monoliths and is user-friendly, and helping protect engineering focus time by systemically solving sources of distraction or mental load with AI.
Carefull - Data Scientist / AI Engineer
Own end-to-end implementation of AI-driven detection features, from discovery to production deployment and iteration. Design and build data enrichment pipelines to extract structured information from messy, real-world financial transaction data. Research fraud and scam typologies relevant to older adults and translate findings into scalable detection logic. Build evaluation frameworks including metrics, error analysis, and model comparisons to measure system performance and drive improvement. Optimize AI pipelines for accuracy, latency, and cost by making informed tradeoffs on model selection and architecture. Collaborate with Customer Service, Go-to-Market, and partner-facing teams to ensure solutions meet real-world needs and deliver measurable impact. Stay current with developments in LLMs, agent architectures, and applied AI to identify practical applications for the domain.
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