Owns the technical direction for large-scale machine learning models, guiding the development of advanced deep learning architectures and high-impact ML systems.
Partners with leadership to define ML roadmaps, drive innovation in scalable model design and training approaches.
Ensures efficient, reliable deployment of ML models in production and mentors the team’s technical capabilities.
Reddit is a community-driven platform where users submit, vote, and comment on topics of interest. With over 100,000 active communities and approximately 126 million daily active unique visitors, it is one of the internet’s largest sources of information.
Design and operate core AI platform components for training, deploying, and serving ML models at scale.
Own model serving and inference workflows end-to-end, optimizing for reliability, latency, throughput, and cost.
Collaborate with product, infrastructure, and security teams to build scalable platform capabilities for AI-powered features.
Mozilla Corporation is the non-profit-backed technology company behind Firefox and Pocket, with over 225 million monthly users. A wholly-owned subsidiary of the Mozilla Foundation, the company is mission-driven, employee-owned, and focused on privacy and open standards.
Own the technical design and delivery of subsystems in a high-throughput, low-latency inference platform.
Develop robust API layers and SDKs that abstract complex distributed inference orchestration.
Build and harden a multi-tenant control plane for metering, rate limiting, and tenant isolation.
Stack develops revolutionary AI and autonomous systems to enhance safety and efficiency in trucking. The team has decades of experience deploying real-world systems and is committed to inclusion, entrepreneurship, and innovation.
Design and implement content discovery algorithms to deliver a highly personalized user experience on Reddit's Notifications platform.
Enhance core recommendation capabilities including candidate retrieval, ranking models, and budget optimization, deploying ML models and integrating LLMs.
Serve as the primary ML domain expert, driving architectural decisions and collaborating with product, infrastructure, and data science teams.
Reddit is a community of communities built on shared interests, passion, and trust, hosting the most open and authentic conversations on the internet. With over 100,000 active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet's largest sources of information.
Build, optimize, and embed machine learning models for on-device inference within the QSIDS detection engine.
Collaborate closely with systems engineers to integrate models efficiently into a Go-based engine.
Take models all the way to production and own them once they're running, monitoring performance, detecting drift, and iterating to keep them reliable.
Qohash builds the zero copy data security control layer for enterprises to adopt AI safely. The company has a strong culture centered on five core values: pursuit of excellence, resilience, mission focus, accountability, and embracing conflict.
Developing and iterating on embedding models for advertising use cases, from aggregation pipelines to sequence models.
Building data processing and inference pipelines and evaluating features through end-to-end experimentation.
Ensuring reliability and scalability of ML systems by writing tests, monitoring, and reviewing code.
Reddit is a platform of communities built on shared interests and authentic conversations. With over 100,000 active communities and 126 million daily active users, it is one of the largest sources of information on the internet.
Design and build scalable ML training, deployment, and inference pipelines using CI/CD and cloud infrastructure.
Implement MLOps for model versioning, monitoring, and automated retraining to detect drift and performance degradation.
Partner with Data Scientists and Product teams to productionise models and integrate ML into customer-facing products.
We develop solutions that make an impact for companies around the globe. Our culture embraces openness, acts with respect, shows grit & guts, and combines employment with enjoyment.
Define, drive, design, and build/ship end-to-end solutions that solve real customer problems.
Contribute to the end-to-end AI/ML software development lifecycle, ensuring reproducible research.
Drive architecture, design, and delivery of advanced ML systems in the Product R&D team.
Kinaxis is a global leader in modern supply chain orchestration. Known for its AI-infused platform and transparency across end-to-end supply chains, Kinaxis helps customers make faster, better decisions. The company has over 2000 employees worldwide and is recognized with Top Employer awards.
Design, train, evaluate, and ship ML systems for governance and security, starting with prompt injection detection and behavioral anomaly detection.
Build supporting infrastructure including data pipelines, feature stores, model serving, and evaluation harnesses.
Set technical direction for ML work, own architecture, evaluation methodology, and model lifecycle.
Docker provides developer tools for building, sharing, and running applications across Docker Desktop, Docker Hub, and Docker Scout. With over 20 million monthly users and a globally distributed remote-first team, Docker is trusted by solo founders to the world's largest companies.
Empower ML Engineers with the tools, infrastructure, and frameworks they need to iterate fast autonomously.
Accelerate time-to-market for production-ready ML products with seamless integration and access to data and resources.
Own ML CI/CD in close collaboration with the DevExp team, adapting existing frameworks to ML-specific needs.
Dailymotion is a video platform designed to broaden users' horizons with a unique algorithm. They foster inclusivity and aim to build a better and safer Internet with cutting-edge solutions for video hosting and advertising. With 400 employees in France, New York, and Singapore, Dailymotion is shaking up the global video platform ecosystem.
Lead and grow a cross-functional team of ML engineers, backend engineers, and data analysts.
Guide research and experimentation, balancing long-term innovation with near-term business impact.
Partner with Product and Engineering leaders to identify opportunities for increasing revenue and conversion through personalization.
Constructor is an AI-first ecommerce search and discovery platform helping shoppers find products and enabling global e-commerce brands to drive revenue and conversion. The company offers a fully remote team, unlimited vacation, and a training budget.
Architect the migration of the existing compiler flow into MLIR, defining dialects, passes, and lowering strategies.
Build conversion paths between MLIR and Mythic’s custom low-level IR to keep both flows operational during migration.
Define validation infrastructure within MLIR, including interpretation or execution paths for simulation and debugging.
Mythic is building the future of AI computing with breakthrough analog technology that delivers high performance at low power and cost. They have raised over $100M from world-class investors and secured multi-million-dollar customer contracts across multiple markets.
Design, develop, and deploy AI/ML models to automate and improve internal workflow.
Build and maintain ML pipelines within an AWS cloud environment.
Integrate ML capabilities into existing Java and React application workflows.
Oddball aims to improve daily lives by delivering quality software to the federal space. With a team of experienced engineering, product, and UX professionals, we value learning, growth, and making a big impact in a rapidly growing company.
Design and develop machine learning solutions ensuring accuracy, performance, security, and scalability
Implement and maintain end-to-end AI/ML pipelines from data ingestion to deployment
Collaborate across planning, design, and code review to raise overall code quality
We shape the future of communications from remote-first environments. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide, with a strong culture of connection and inclusion.
Build and operate the real-time inference service for the risk decision engine with low latency and high availability.
Own model deployment infrastructure including CI/CD, shadow mode, and staged rollouts.
Build model observability and partner with Risk Data Science for production operation.
Mercury is a fintech company that provides banking services for startups via partner banks. The company is committed to creating a safe environment and values diversity, with a growing team focused on innovation.
Benchmark FP8 quantization across GPU families and ship a production config to achieve speedup.
Evaluate serving frameworks with speculative decoding to improve performance.
Build a fine-tuning pipeline to enable faster model training and deployment.
Fathom eliminates the needless overhead of meetings with an AI assistant that captures, summarizes, and organizes key moments. They are a small company that creates magical experiences through focused builders and values a supportive environment.