Build and improve ML/CV models, including retraining and optimizing for Samsara-specific problems.
Work with petabyte-scale data from camera and sensor devices to develop new models.
Partner with firmware and full-stack teams to deploy models for optimal performance and cost.
Samsara is the pioneer of the Connected Operations Cloud, enabling organizations to harness IoT data for actionable insights to improve safety, efficiency, and sustainability. As a public company with over 2.3 million IoT devices deployed globally, Samsara fosters a culture of growth mindset, inclusivity, and teamwork.
Design and train custom object detection models for retail environments.
Fine-tune and deploy vision-language models for product understanding and scene reasoning.
Optimize models for edge deployment using quantization and pruning techniques.
Panoptyc is building the future of retail intelligence through computer vision and AI. The company has a focused, collaborative team of engineers working on cutting-edge retail applications.
Design, build, and optimize data workflows for Machine Learning and GenAI solutions in cloud environments.
Develop and deploy Machine Learning and Generative AI models using AWS SageMaker.
Create and manage data and model pipelines to improve the efficiency of AI and machine learning systems.
Netrix Global provides the people, processes, and technology to run and scale modern data-driven businesses. It is a top system integrator with a culture focused on ownership, teamwork, and respect.
Design, build, deploy, and optimize machine learning models that process large volumes of complex, unstructured data.
Develop and maintain scalable ML pipelines capable of supporting millions of documents and diverse customer requirements.
Lead technical initiatives from early experimentation through production implementation and ongoing improvement.
The company develops intelligent automation solutions using AI and machine learning for large-scale document processing. It offers a highly autonomous engineering environment with a focus on continuous improvement and innovation.
Develop end-to-end data processing pipelines for display characterization and machine learning algorithms for visual artifact detection.
Design and implement anomaly detection models and automated analysis tools for display performance.
Collaborate with cross-functional hardware teams and maintain data infrastructure for ML workflows.
itD is a consulting and software development company that blends diversity, innovation, and integrity. It is a woman- and minority-led firm with a flat structure and a focus on delivering excellent results.
Architect end-to-end computer vision pipelines for real-world safety detection, including object detection, tracking, and semantic segmentation.
Drive the technical roadmap for edge and cloud perception, optimizing models for constrained hardware without sacrificing accuracy.
Mentor senior scientists and engineers, translating customer needs into precise engineering challenges.
Samsara is the pioneer of the Connected Operations™ Cloud, a platform that enables organizations dependent on physical operations to harness IoT data for actionable insights and improved safety, efficiency, and sustainability. As a recently public company, they foster a culture of rapid career development, collaboration, and innovation while scaling globally.
Assist in developing computer vision models for wildfire detection and environmental monitoring.
Help implement and maintain ML/CV pipelines and deploy models on NVIDIA Jetson edge platforms.
Collaborate with AI researchers, software engineers, and product teams to optimize and document solutions.
Pano AI is the leader in AI-powered wildfire detection and intelligence, helping fire professionals detect, respond to, and contain wildfires faster and more safely. We are a team of more than 175 people working in a hybrid-remote environment across North America and Australia, with headquarters in San Francisco.
Develop, deploy, and maintain production-grade Machine Learning models in cloud environments.
Build, maintain, and optimize data pipelines and monitor model performance post-deployment.
Partner with engineering, data, and business stakeholders to translate goals into scalable ML solutions.
In All Media is a global technology and design firm building impactful digital solutions through remote, distributed teams across LATAM. They partner with international clients across industries, providing long-term technical expertise and team augmentation.
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.
Own tracking and reporting of CV accuracy metrics, investigating misclassifications and identifying patterns across customers.
Curate, label, and prioritize datasets for model retraining, partnering closely with ML and CV engineers.
Build and improve the continuous learning pipeline, moving from flagging issues to fixing them directly.
We are building the backbone of freight by reinventing supply chain infrastructure with carrier agnostic truck terminals. We are a vertically integrated real estate, operations, and technology company backed by $1B, scaling to build the most valuable logistics network in the country, with a culture of accountability, integrity, and high performance.
Develop, train, and evaluate machine learning models to support product objectives.
Prepare, clean, and analyze datasets for model training and validation.
Deploy, monitor, and improve machine learning models in production environments.
The partner company develops AI-powered products to solve real-world challenges. They offer a fully remote, flexible work environment with a focus on innovation and collaboration.
Design, develop, train, and evaluate machine learning models for interpreting complete CT studies.
Research foundation-model approaches for medical imaging, including 3D and volumetric learning at large scale.
Develop vision-language models connecting medical images with radiologist terminology and reporting patterns.
Our partner is a research-driven team building next-generation AI models to understand complete CT studies. They work with a dataset of approximately 10 million patients and collaborate with fellowship-trained radiologists across multiple specialties.
Own core computer vision models from 3D human pose to body modeling, shipping them to production.
Manage the full data lifecycle including training frameworks, annotation workflows, and evaluation pipelines.
Extend movement understanding into multimodal AI and automate model training and deployment systems.
Sword is building AI to heal billions, pioneering an AI-native care platform that delivers personalized, connected healthcare without traditional barriers. Backed by $500M and with over 1 million members and 2,000+ enterprise clients, Sword is a fast-growing frontier AI lab with a culture of clinical rigor and AI fluency.
Design and implement cloud/edge AI architectures for real-time computer vision applications.
Develop computer vision models for wildfire smoke detection, vegetation classification, asset detection, and spatial reasoning.
Port and optimize deep learning models for ARM64, CUDA, TensorRT, ONNX, and NVIDIA Jetson platforms.
Pano AI is a leader in AI-powered wildfire detection and intelligence, helping fire professionals detect, respond to, and contain wildfires faster. Our team of 175+ works in a hybrid-remote environment across North America and Australia, based in San Francisco.
Design, train, and ship ML systems for governance and security like anomaly detection and trust scoring.
Build data pipelines, model serving, evaluation frameworks, and feedback loops.
Set technical direction, own architecture, and help recruit and mentor as the team grows.
Docker provides developer tooling trusted by over 20 million monthly users and billions of container pulls. They are a globally distributed, remote-first team building tools for software delivery.
Develop, deploy, and maintain machine learning models in production environments using AWS SageMaker or similar platforms.
Perform exploratory data analysis, feature engineering, and build data pipelines to support scalable ML workflows.
Monitor production models, address performance issues, and collaborate with engineering and business stakeholders to deliver data-driven solutions.
Google is a global technology company that develops products and services to organize information and make it universally accessible and useful. The company is a large multinational with a culture focused on innovation, collaboration, and data-driven decision-making.
Passionate about building AI models from the ground up and deploying them in production
Excited about joining early-stage startups and working directly with founders
Interested in shaping AI strategy and leading the development of AI-powered products
SignalFire partners with top early-stage startups shaping the future of technology. They have a portfolio of over 200 innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
Build the environments and verifiers our models train against
Own the synthetic data pipeline, from generation through quality gates
Ship models into production and keep improving them on real usage
LiveKit builds the infrastructure layer for the voice-driven era of computing, enabling developers to build, deploy, and scale voice AI applications. Founded in 2021, they power voice AI for major companies and have a small, senior team that values craft and creativity.
Design and implement advanced knowledge distillation pipelines, including teacher-student approaches and multi-teacher architectures.
Run large-scale machine learning experiments to optimize model quality, latency, efficiency, and cost trade-offs.
Collaborate with research teams to transform emerging distillation techniques into reliable production-ready implementations.
Our partner is an innovative company focused on advancing the efficiency and scalability of next-generation machine learning systems. They offer a remote-friendly work environment with an async-first culture and a small, senior team combining research expertise and engineering excellence.
Train, evaluate, and iterate on ML models for customer feedback, including custom fine-tuning pipelines.
Build and maintain LLM-powered features like retrieval pipelines and insight agents.
Design and run robust evaluation frameworks to measure model performance.
Chattermill helps large brands like Uber, Amazon, and Wise put customers at the center using AI. They offer a flexible, trust-based culture with a choice-first environment.