Join an international, results-driven team working at the intersection of machine learning, cloud infrastructure, and high-quality software development. Youβll play a key role in taking projects from proof-of-concept to production, writing robust, scalable, and clean Python code. Design and implement end-to-end solutions. Contribute to DevOps workflows to streamline CI/CD, monitoring, and deployment.
Job listings
As a Staff Backend Engineer on the Ads Creative Management team, you will build tools that make it easier for advertisers to create relevant, effective, visually pleasing ads on Reddit. The ideal candidate will leverage their knowledge of asset storage and management, AI/LLMs, and scaling services to develop world-class tooling and innovate on the behalf of our advertising partners.
Design, build, and maintain scalable full-stack applications and services within The Zebra. Collaborate with product managers, designers, and other engineers to define and deliver new features. Develop clean, reusable, testable code across backend and frontend codebases. Drive technical design and architecture discussions.
As the AI Safety Principal Engineer, you will be a technical leader with extensive experience in the full end to end development lifecycle for artificial intelligence & machine learning. Guide the develop of GMβs AI safety strategy, stay current on industry best practices and standards. This role requires extensive programming and statistical techniques to solve complex problems and provide safety guidance to the engineering development teams that are focused on AI/ML.
Design, build, and maintain the technical infrastructure that powers Swing Left and Vote Forwardβs programs, ensuring our digital tools effectively support volunteer action and organizational goals. This role leads the implementation of software solutions across swingleft.org, votefwd.org, and related platformsβdeveloping reliable, scalable code and managing integrations with grassroots organizing tools and data providers. Collaborate closely with product, analytics, and program teams to drive the product development lifecycle, support experimentation, and continuously improve user experiences.
Develop features for the chDB core engine in C++, working on areas like performance optimization, object serialization, and DataFrame operations. Design and implement language bindings for various programming languages. Closely collaborate with our integration teams to ensure seamless compatibility across language ecosystems, particularly with data science tools and frameworks.
Join the OpenTelemetry team at New Relic and contribute to developing, maintaining, and enhancing New Relic's OpenTelemetry offerings. Work closely with experienced engineers to solve complex technical challenges and build reliable, scalable software. Responsibilities include participating in design, development, and testing of OpenTelemetry components and integrations, writing clean code, and collaborating with team members.
SandboxAQ's AI Team is seeking a highly accomplished, veteran software engineer to design and rapidly prototype AI-first SaaS products incorporating Large Quantitative Models (LQMs) and agentic frameworks. A successful candidate must be comfortable owning the end-to-end lifecycle of both internal and external facing software systems and applications and have significant industry experience bringing products from conception to production and deployment.
As an engineer on the team, youβll play a critical role in designing, building, and deploying AI-powered features that directly impact how users experience and interact with our platform. Youβll work across systems leveraging state-of-the-art tools and infrastructure to deliver intelligent, scalable customer support solutions. Our tech stack leverages modern technologies, including Docker, Kubernetes, Redis, MongoDB, and ElasticSearch.
PHIL is seeking a talented and experienced Staff Software Engineer to lead the technical vision and implementation of intelligent agents across our operational platform. This role will focus on leveraging large language models (LLMs) to optimize key pharmacy workflows, automate manual processes, and summarize complex documentation to support faster, higher-quality decision-making by internal teams.