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.
Freelance AI Evaluation Engineer (Python/Full-Stack)
Create challenging coding test cases to push AI coding systems to their limits by reviewing and refining realistic coding tasks based on provided production codebases with realistic scope, requirements, and information sources. Write comprehensive functional tests that validate actual end-to-end behavior and edge-cases. Craft challenges that are fair but hard, where the AI has all the context it needs, requiring complex reasoning with information scattered across files and external sources. Analyze AI failures to understand the model's struggles and strengths. Iterate based on feedback from expert QA reviewers who score work on seven quality criteria.
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.
Full-stack Developer (Full-Time/Intern) - SH 全栈工程师 (全职/实习) - 上海
As a Full-Stack Engineer at Flowith, you will be responsible for independently or collaboratively leading the full-stack development of Flowith's core modules crossing front-end and back-end boundaries to deliver highly available and scalable system code. You will deeply integrate advanced AI algorithms and complex models into the product flow to create intelligent interactive experiences, work closely with product managers, designers, and AI engineers in a creative environment to implement innovative AI concepts, automate deployments and manage continuous integration on mainstream cloud infrastructure while monitoring and optimizing system performance and resource usage. Additionally, you will participate in the design evolution of the core architecture, conduct in-depth code reviews, and help accumulate technical components and best practices to elevate the engineering standards of the team.
Head of Product, AI
Own the end-to-end AI product strategy, grounded in technical feasibility and real-world constraints. Translate model capabilities, data limitations, and evaluation results into clear product decisions. Make hard trade-offs across quality, latency, cost, reliability, and user experience. Work daily with ML, backend, and mobile engineers on design, evaluation, and iteration. Define success metrics and feedback loops across offline evaluation, online experiments, and human feedback. Drive execution with clear specifications, risk awareness, and disciplined prioritization. Ensure AI features ship quickly, safely, and reliably into production. Own AI product quality across UX, correctness, and outcomes.
Senior ML Operations (MLOps) Engineer
The Senior ML Operations (MLOps) Engineer at Eight Sleep is responsible for introducing and implementing cutting-edge ML technologies, owning the design and operation of robust ML infrastructure including scalable data, model, and deployment pipelines to ensure reliable model delivery to production. They collaborate cross-functionally with R&D, firmware, data, and backend teams to ensure reliable and scalable ML inference on Pods. They optimize ML systems for cost, scalability, and performance across training and inference, and develop tooling, microservices, and frameworks to streamline data processing, experimentation, and deployment. The role requires effective communication in a remote work environment.
Manual Quality Assurance Engineer, Web Core Product
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Backend Engineer, AI
Build and operate backend systems that serve AI-powered features in production; design inference pipelines, orchestration layers, and service boundaries around models; own production concerns including monitoring, logging, alerting, and incident response; optimize latency and throughput across inference, caching, batching, and streaming.
Safety Engineer
The AI Safety Engineer is responsible for designing and building scalable backend infrastructure for content moderation, abuse detection, and agents guardrails by deploying AI/ML models into production systems. They will architect robust APIs, data pipelines, and service architectures to support real-time and batch moderation workflows. The role includes implementing comprehensive monitoring, alerting, and observability systems, establishing SLIs, SLOs, and performance benchmarks. The engineer will collaborate with ML engineers to translate research models into production-ready systems and integrate them across the product suite. Additionally, they will drive technical decisions and contribute to the vision for the safety roadmap to build next-generation platform guardrails for scale and precision.
Access all 4,256 remote & onsite AI jobs.
Frequently Asked Questions
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.