Build product surfaces across web, desktop, and mobile for Hermes Agent and Nous Portal.
Develop backend services and APIs that hold up under real usage.
Maintain the cloud platform and infrastructure behind products and model serving.
Nous Research builds AI infrastructure including Hermes Agent and Nous Portal. The team is small, fast-moving, and values generalist engineers with strong ownership and low ego.
Lead the development of Retide's aerial perception capabilities, building detection and segmentation models from real-world drone and beach imagery.
Travel to Brazil, Canada, and Southeast Asia for field deployments, working alongside cleanup partners to test models outside the lab.
Own the full perception stack including multimodal sensor fusion, edge AI, active learning, and human-in-the-loop systems.
Retide builds AI and robotics infrastructure to help organizations understand and measure plastic pollution in the ocean. It is a pre-seed Canadian ocean-tech startup with a small, ambitious team that values curiosity, ownership, and progress over perfection.
Develop and scale latent video diffusion models for human-centric video generation.
Lead end-to-end applied research and engineering projects from hypothesis to production.
Optimize distributed training and inference for large-scale deployment.
They develop production-grade foundation models for human-centric video generation. The team operates in a high-ownership, fast-paced environment with a focus on safety and ethics.
Partner with interdisciplinary teams to develop novel AI strategies for antibody design, including test-time compute and multi-objective optimization.
Analyze validation results to iteratively improve design and evaluation methodologies.
Publish high-impact research to advance Absci's position as a thought leader in AI antibody design.
Absci is a clinical-stage biotechnology company using generative AI to design novel therapeutics. It is a global company with offices in the US, Switzerland, and Serbia, offering a collaborative and innovative culture with access to advanced compute resources and a wet lab.
Provide technical leadership and mentorship to MLEs, driving strategy, designs, and best practices in analysis, modeling, and engineering.
Develop new or iterate on existing embedding models for advertising use cases, including aggregation pipelines, two-tower architectures, and sequence models.
Ensure reliability, scalability, and performance of ML systems through automated tests, monitoring, and best practices for model management.
Reddit is a community of communities built on shared interests, passion, and trust. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet's largest sources of information, operating with a flexible first workforce.
Build and deploy production-grade LLM inference systems from scratch, owning the pipeline from query to response.
Optimize inference workloads for latency, throughput, and cost using tools like vLLM, SGLang, and TensorRT-LLM.
Collaborate with the CTO and Product to define the technical roadmap for inference infrastructure as the organization scales.
The company is an open-source-oriented startup building production-grade inference infrastructure for large language models. It is a remote-first, globally distributed team that values engineering ownership, speed, and customer impact.
Build, adapt, and operationalize ML models to estimate forest structure from remote sensing data.
Integrate trained models into automated production pipelines and maintain surrounding data infrastructure.
Contribute to scientific manuscripts and serve as a cross-team link between SciDev and Data Engineering.
Vibrant Planet is a team of leaders in fire science, applied science, forestry, policy, and tech that uses a cloud-based AI-driven platform to lower wildfire risk. The company is backed by climate and resilience leaders and values an inclusive, equitable work environment.
Develop and deploy machine learning and AI systems.
Work with LLMs, generative AI, and modern ML frameworks.
Optimize model performance, latency, and cost.
A fast-growing technology company building critical infrastructure that powers high-volume, real-time business operations across multiple systems and platforms. It is a collaborative, fast-moving environment where engineers have meaningful influence on architecture and product direction.
Design and optimize training and post-training pipelines for large language models.
Improve model quality through supervised fine-tuning, reinforcement learning, and evaluation.
Build PyTorch-based training infrastructure and optimize distributed training across multi-GPU environments.
Lightning AI builds an end-to-end platform for developing, training, and deploying AI systems, founded in 2019. They are a global company with offices in New York, San Francisco, Seattle, and London, backed by major venture capital firms, and foster a builder culture that values urgency, ownership, and open communication.
Design, train, and improve large-scale machine learning models for recommendation and personalization, leveraging modern deep learning architectures.
Own end-to-end delivery of major ML system components, from problem framing to production rollout, with cross-functional partners.
Optimize distributed training, model efficiency, and online inference performance while ensuring low-latency, high-throughput production systems.
Reddit is a community of communities built on shared interests, passion, and trust, hosting authentic conversations. With over 100,000 active communities and about 130 million daily active users, Reddit is one of the internet's largest sources of information.