Build and improve computer vision and 3D perception models that detect and assess infrastructure from LiDAR and imagery.
Develop LLM-powered products like agentic workflows, MCP servers, and AI copilots for customer tools.
Own models end-to-end, from data and training through evaluation, deployment, and monitoring in production.
Cyvl is a Physical AI company building purpose-built sensors, computer vision, and AI to turn every drive into current data for infrastructure. We're a fast-moving Boston startup with 500+ cities using our platform, and a culture of ownership, intensity, and care.
Monitor and synthesize trends across AI and machine learning research, foundation models, agents, and data enrichment methods.
Tinker with emerging models, tools, and datasets to build prototypes and run experiments that turn ideas into evidence.
Identify high-leverage opportunities to enrich data assets and translate research into actionable recommendations.
Troveo builds the data platform AI labs need to train next-generation models, with the world's largest licensed platform of scarce, proprietary data. It is a small, high-impact team backed by top investors, focused on transparency and work-life balance.
Architect and implement state-of-the-art GenAI pipelines for ad creative generation, including brand asset preservation and image/video editing.
Fine-tune large vision-language models and build feedback loops using ad performance metrics (CTR, CVR) via RLHF/RLPF.
Partner with Product, Sales, Policy, and Ads ML teams to integrate creative capabilities into Ad Manager and ensure brand safety.
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, it is one of the internet's largest sources of information.
Lead exploration and application of Large Language Models and Generative AI into core product lines.
Translate the latest research into high-performing systems that enhance customer experiences.
Collaborate with cross-functional teams to set strategy and deploy ML solutions with real business impact.
Replicant is the industry leader in voice AI for customer service, providing automated phone bots for enterprises like AAA and Fanatics. Founded in 2017, the company is backed by top-tier Silicon Valley investors, has offices in the SF Bay Area, Toronto, and New York, and maintains a distributed team across the US and Canada.
Conduct research to develop new functionalities and improve existing technologies across fraud, voice/speech, video, authentication, and deepfake detection.
Design, implement, and evaluate deep learning algorithms and ML models tailored to complex datasets.
Partner with research and engineering teams to transition prototypes into production-ready systems and publish findings in top conferences.
Pindrop is a cybersecurity company delivering continuous identity verification across voice, video, and digital interactions. Backed by leading investors and protecting billions of interactions annually, we maintain a remote-first culture and focus on innovative security research.
Build the component layer around our layout synthesis engine, including API contracts, services, and evaluation gates.
Turn model retraining into a one-command job with built-in benchmarks and readable results for the whole team.
Own latency and cost budgets for learned capabilities and partner with infrastructure engineers on MLOps and deployment.
Higharc is a VC-backed startup that is changing how new homes are designed and built using spatial AI and generative floor plan technology. The company is fully remote, has raised over $175M, and values flexibility, collaboration, and asynchronous deep work.
Design, scale, and deploy production-ready computer vision and ML architectures for satellite imagery.
Lead full-lifecycle model R&D from data curation through training, validation, and error analysis.
Drive model robustness across challenging real-world conditions and optimize AWS GPU workloads.
BlackSky is a real-time intelligence company that operates a space-based intelligence platform providing satellite imagery, automated analytics, and monitoring for national security and commercial customers. Its global team is people-first, customer-focused, and works with cutting-edge technology to deliver foresight and strategic advantage.
Lead development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data.
Build interpretable, well-calibrated models and drive new methods from prototype through scalable implementation to clinical validation.
Collaborate with molecular biologists and clinical experts and mentor junior scientists.
Natera is a global leader in cell-free DNA testing, dedicated to oncology, women's health, and organ health. The team consists of highly dedicated professionals from world-class institutions who care deeply for the work and each other.
Learn, maintain, and improve our synthetic data pipeline and automated training system.
Take over a model and improve it with an agent loop that generates its own data.
Build closed loops where agents train detectors, test against validation sets, and improve with little human input.
CVEDIA builds computer vision models and applications that run on server and edge hardware using synthetic data. We are a small, fully remote team that uses AI agents across the company.
Design and implement state-of-the-art ML models and training pipelines for robotics.
Develop efficient data/training strategies and evaluation frameworks for rapid experimentation.
Collaborate with engineering to optimize training infrastructure and deployment.
We're revolutionizing real-world automation by making robotic systems accessible to everyone. Our AI-powered platform brings software automation to physical spaces, and we're a small startup team working across the stack to solve customer problems.
Build and extend pretraining code to scale experiments into full training runs.
Evaluate model architecture changes and optimize training throughput and resilience.
Run controlled ablations and collaborate with data and evaluation researchers.
Prime Intellect is building an open superintelligence stack, providing the infrastructure and platform for frontier AI training and deployment. The company has raised $150M from top investors and boasts a mission-driven team working to decentralize AI.
Develop AI-based biomarkers using multimodal data including whole-slide images, clinical variables, and molecular data to predict patient outcomes and treatment benefit.
Contribute to self-supervised foundation models and downstream ML models such as multiple-instance learning, survival analysis, segmentation, and classification.
Improve model robustness and interpretability across scanners, institutions, and patient populations to build clinician trust.
Artera is an artificial intelligence company dedicated to transforming cancer care by developing foundation models that analyze clinical and pathology data to guide therapy selection. They value diversity and collaboration, offering a supportive remote culture with unlimited PTO and equity as core compensation.
Develop deep learning models for feature matching, depth estimation, pose estimation, and image-to-map localization.
Own data preparation and supervision strategies, including dataset curation, labeling workflows, and quality checks.
Collaborate with state estimation and deployment engineers to integrate learned measurements into VIO and terrain-relative navigation systems.
This company builds autonomous systems that can understand motion and localize themselves when GPS is unavailable. Its engineering team works remotely, collaborating across deep learning, computer vision, and state estimation.
Develop and evaluate deep learning models for feature detection, matching, depth estimation, and visual localization.
Own data preparation, training workflows, and evaluation of learned components for vision-based navigation.
Partner with state estimation and deployment engineers to integrate and optimize models for onboard systems.
Shield AI is a venture-backed defense-tech company developing intelligent systems to protect service members and civilians, with products like Hivemind autonomy software and V-BAT aircraft. It has offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, actively supporting operations worldwide.
Lead the end-to-end machine learning lifecycle, from data preparation and model training to evaluation, inference, and deployment.
Build and optimize scalable training, fine-tuning, and inference pipelines for large-scale models on GPU infrastructure.
Establish production best practices for model quality, reliability, safety, and measurable performance improvements.
This company builds production-grade machine learning systems and large-scale GPU-powered inference pipelines. It is a fully remote team that values technical rigor, collaboration, and hands-on engineering.
Build post-training and evaluation systems for multimodal agents operating browsers and desktops.
Turn real workflows into environments, rewards, and experiments that drive reliable agent improvement.
Work directly with customers and research partners while maintaining a substantive research agenda.
Prime Intellect is building the open superintelligence stack, providing infrastructure for post-training frontier AI models. The company has raised $150M in funding and fosters a culture of ownership and collaboration for ambitious AI teams.
Design, deploy, and optimize large-scale ML systems for retrieval, ranking, and LLM-powered features.
Lead ML projects from concept to production, improving answer relevance and user experience.
Collaborate with Product, Data Science, and Engineering teams to shape technical direction.
The hiring partner is a technology company focused on building advanced AI systems that help users discover relevant answers from large collections of online conversations. It values innovation, collaboration, and responsible AI development, offering a remote work environment within the United States.
Develop deep understanding of customer problems and map them to Cohere solutions as a trusted technical advisor.
Lead design and deployment of customer pilots, owning the technical narrative from discovery to business case.
Collaborate with Product and Engineering teams and partners to scale solutions and gather customer feedback.
Cohere is a leading security-first enterprise AI company building cutting-edge foundation AI models and products for real-world business problems. It is a global team of researchers, engineers, and designers headquartered in Toronto with offices worldwide, committed to driving AI adoption.
Build AI applications, agents, skills, connectors, and workflow automations that solve business problems.
Translate ambiguous business needs into AI-native workflows and own engineering from discovery to production launch.
Work closely with internal teams to embed AI solutions and drive measurable gains in quality, speed, and cost.
Reddit is a community of communities built on shared interests, passion, and trust. With 100,000+ active communities and about 130 million daily active visitors, it is one of the internet's largest sources of information.
Research and develop new methods that push the frontier of Speech AI.
Improve data quality, build evaluation harnesses, and analyze production model accuracy.
Partner with researchers and engineers to turn research prototypes into production-ready systems.
AssemblyAI builds best-in-class Voice AI models powering next-generation voice applications. With under 100 employees, the company is lean, capital-efficient, and meritocratic, giving every team member outsized ownership and impact.