Research Intern, Inference (Fall 2026)
As an AI Infrastructure Engineer at Together, the responsibilities include participating in on-call rotation to respond to production incidents, building and running infrastructure using Ansible, Terraform, and Kubernetes to support scaling to a large number of concurrent users, building monitoring systems to ensure high-quality service, designing and implementing operational processes such as deployments and upgrades, debugging production issues across all services and stack levels, identifying improvements for product architecture in terms of reliability, performance, and availability, and planning the growth of Together AI's infrastructure.
Member of Technical Staff (Machine Learning Engineer)
Translate cutting-edge research into production-ready machine learning systems. Design, build, and deploy end-to-end ML models and pipelines. Develop and optimize models for image and video processing. Own the full ML lifecycle including experimentation, training/fine-tuning, evaluation, and deployment. Rapidly prototype using open-source models and adapt them for product needs. Conduct experiments, analyze results, and iterate to improve performance. Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale. Participate with advancements in machine learning and apply them to continuously improve products.
Warehouse Supervisor (Temporary)
Utilize proprietary software to provide accurate input and labels for healthcare and administration projects, ensuring high-quality data for AI model training. Deliver curated, high-quality data for scenarios involving patient care coordination, medical billing, administrative workflows, and healthcare operations. Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies. Assist in designing and improving efficient annotation tools tailored for healthcare and administration data. Select and analyze complex problems in healthcare and administration fields aligned with your expertise to enhance AI model performance. Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.
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.
Mid/Senior AI Cinematic Video Editor (Full Remote - Worldwide)
Conceptualise scripts based on current production needs centered around existing AI characters. Create narrative-driven, longform video content including stylized and explicit NSFW visuals with focus on storytelling, atmosphere, and visual coherence. Own and manage end-to-end AI video production workflows from ideation and prompting to generation, editing, and post-production. Work extensively with ComfyUI pipelines, building, customizing, and optimizing node-based workflows for image and video generation. Utilize tools such as Stable Diffusion (AUTOMATIC1111), ComfyUI, Runway, Pika, and other AI video platforms to produce high-quality visual sequences. Develop and maintain consistent character appearance, style, and scene continuity across longer narratives. 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. Continuously refine workflows for efficiency, scalability, and output quality.
Applied AI Engineer
As an Applied AI Engineer, you will turn model capabilities into real product behavior by owning problems end-to-end, from shaping model behavior to building the systems around it and ensuring reliable performance in production. Responsibilities include building and shipping AI features end-to-end (model to system to user experience), designing and iterating on prompts, tools, memory, and agent workflows, turning raw model outputs into structured, reliable, and predictable behaviors, debugging issues across the full stack (model, orchestration, infrastructure, user experience), optimizing for latency, cost, and production reliability, developing lightweight evaluation frameworks to measure real-world performance, and working closely with product and engineering teams to translate ambiguous problems into working systems.
Backend Engineer, AI
As a Backend Engineer, AI, you own the inference and orchestration layer that powers every AI interaction in the product. You build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients. Responsibilities include building and operating backend systems that serve AI-powered features in production, designing inference pipelines, orchestration layers, and service boundaries around models, owning production concerns such as monitoring, logging, alerting, and incident response, and optimizing latency and throughput across inference, caching, batching, and streaming.
Head of Internal Tools Engineering
The role involves architecting, building, and scaling the internal technology ecosystem to accelerate workforce productivity, eliminate operational friction, and provide a compounding infrastructure advantage by treating internal tools with product rigor and user-centricity. Responsibilities include owning the end-to-end strategy and roadmap for all internal tools, platforms, and automation; making strategic build-vs-buy decisions; mapping current and next-state process flows and leading systems transformation. The role requires architecting and maintaining the full engineering lifecycle of internal platforms, building API-first ecosystems integrating with various business systems, owning system reliability and operational resilience, and designing scalable, secure cloud-native architectures. The role leads AI adoption and automation integration into internal workflows, including deploying intelligent automation tools, evaluating AI-assisted troubleshooting, and driving continuous experimentation with prototypes. The person will reduce cognitive load for internal users by providing golden paths and standardized workflows, ensuring frictionless onboarding, and measuring platform success via adoption rates, user satisfaction, DORA metrics, and productivity impact. Team leadership duties include building, leading, and mentoring engineers and managers, fostering a collaborative culture rooted in ownership, speed, craftsmanship, and psychological safety. The role partners cross-functionally with various company leadership teams to translate business needs into a unified technical vision, aligning internal platform investments with company strategy and demonstrating measurable ROI.
Chief Technology Officer
The Chief Technology Officer will define the long-term architecture for A1’s AI systems, infrastructure, and developer platform, evaluate trade-offs between speed of iteration and long-term system design, and ensure systems are designed for scalability, reliability, and long-term evolution. They will guide key decisions across model integration, data pipelines, distributed systems, and product architecture. The CTO will work with engineers to translate product direction into clear technical execution, help structure engineering workstreams and keep teams aligned on priorities, maintain high engineering standards while focusing on shipping, and establish engineering culture, development practices, and technical standards. Additionally, they will build and scale a world-class engineering team across key talent hubs including China and the US, identify strong technical leaders, define hiring standards and interview processes, work closely with product, research, and leadership teams, ensure technical workstreams move forward smoothly across teams and locations, and help resolve cross-team technical and execution challenges.
Android Developer FT - Shanghai 安卓工程师 (全职) - 上海
Design and develop Flowith's Android platform products, focusing on architecture design and core development to ensure optimal app performance. Implement and optimize AI features for mobile applications, integrating advanced AI capabilities deeply on mobile devices. Collaborate with product, design, and backend teams to create exceptional user experiences that cross technical and business boundaries. Explore and implement cutting-edge Android technologies and frameworks continuously. Conduct code reviews and performance optimizations to maintain high code quality. Participate in Vibe Coding sessions, dedicating 70% to 99% of time to collaborative programming in a creative and dynamic environment.
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