Build and maintain core technology behind next-generation Linux software distribution through snapd, focusing on secure, reliable application delivery.
Debug and resolve complex system-level issues across Linux environments, ensuring stability, security, and performance.
Contribute to secure software delivery mechanisms including confinement, sandboxing, and container-like isolation technologies.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies by analyzing applications against core requirements. They operate globally with a distributed team and focus on fair, efficient hiring processes.
Explore and prototype blockchain-based use cases across diverse business scenarios, building experimental tools and proof-of-concepts.
Research on-chain ecosystems, protocols, and industry trends to identify opportunities for scalable adoption.
Transform research outputs into structured technical documentation and actionable recommendations for engineering and product teams.
Jobgether uses AI-powered matching to connect candidates with hiring companies. They operate a remote-first platform focused on efficient and fair recruitment.
Build and operate production-grade model serving infrastructure using vLLM, TGI, or Triton frameworks.
Design and implement auto-scaling, multi-model architectures, and intelligent request routing for ML inference.
Optimize GPU utilization, memory efficiency, and observability to ensure low-latency, cost-effective systems.
They are a distributed cloud infrastructure startup building AI-native cloud services with GPU-powered compute. The company is well-funded, fast-scaling, and operates in a remote-first environment with a focus on sustainability and decentralization.
Design and implement end-to-end agentic AI solutions using serverless AWS architecture and Amazon Bedrock.
Build production-grade AI applications and RAG pipelines, integrating enterprise systems like NetSuite and Salesforce.
Develop responsive frontend applications with React and maintain observability-rich backend services.
Our partner is a technology company focused on building next-generation agentic AI systems for enterprise customers. They offer a collaborative, high-performance engineering environment with exposure to cutting-edge AI technologies.
Design and develop backend services and automation tools for satellite mission operations.
Build and enhance RESTful HTTP APIs and improve existing software architecture.
Deploy and support reliable infrastructure for mission-critical distributed applications.
Our partner operates an advanced fleet of satellites and builds mission-critical software for real-time spacecraft monitoring and automation. They foster a collaborative engineering environment focused on innovation, knowledge sharing, and continuous improvement.
Lead a distributed engineering team to deliver reliable, secure, and scalable cloud infrastructure solutions.
Drive the design, development, and delivery of cloud image pipelines and infrastructure automation using Python and Golang.
Mentor engineers, perform code reviews, and champion agile practices and engineering best practices.
The company develops and manages public cloud infrastructure solutions, focusing on reliable, secure, and scalable cloud-native software and automation. It operates with a distributed, remote-first engineering team that fosters collaboration and technical excellence.
Lead and scale the Forward Deployed Engineering and Technical Support teams, defining engagement models and operating standards.
Own the FDE engagement lifecycle from technical discovery to deployment guidance, ensuring customer value.
Drive operational discipline across support tools and partner with Sales, Product, and Engineering on roadmap alignment.
Runpod is the AI Developer Cloud. More than one million developers use the platform to experiment, train, deploy, and scale AI, and we are a small, remote-first team that has processed over 20 billion inference requests and closed a $100M Series A.
Design, build, and maintain scalable machine learning infrastructure on AWS, including training and deployment pipelines.
Develop and deploy ML models for recommendation systems, fraud detection, credit risk, and personalization use cases.
Implement monitoring, logging, and alerting systems to ensure model performance, stability, and reliability in production.
Our partner is a fast-growing, innovation-driven company where machine learning and AI systems directly power large-scale fintech and commerce experiences. They foster a highly dynamic environment with strong emphasis on experimentation, rapid iteration, and measurable business impact.
Provide technical leadership and mentorship to junior engineers on the Applied AI team.
Design and implement scalable architectures for LLM-based applications, including agents and vector databases.
Develop evaluation pipelines and prototype components to validate AI product concepts.
Jobgether is an AI-powered job matching platform that connects candidates with hiring companies. They prioritize fair and efficient recruitment, fostering an inclusive and diversity-driven workplace culture.
Develop and operate production-ready AI and machine learning systems for enterprise-scale products.
Build and optimize LLM-powered applications, RAG pipelines, and intelligent agents.
Implement software engineering best practices for AI development including CI/CD and testing.
Our partner is building enterprise-grade AI solutions that deliver measurable business impact. They offer a remote-friendly work environment with a collaborative engineering culture focused on innovation, quality, and continuous learning.