Define and execute a comprehensive data strategy for AI model training, simulation, and production deployment in safety-critical autonomous systems.
Own the end-to-end data pipeline from raw collection and labeling through curation, versioning, and delivery at scale.
Build and maintain data flywheels and lead a team of data and infrastructure engineers.
Merlin is a publicly traded aerospace and defense company building the Merlin Pilot, a non-human pilot system delivering full-stack autonomy for any aircraft. Headquartered in Boston, Merlin is a small, innovative, and team-focused startup-like environment that supports professional development.
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.
Build and optimize RL infrastructure for large-scale training.
Improve efficiency across compute, memory, networking, and scheduling.
Design low-level optimizations, from kernels to runtime.
Prime Intellect builds the open superintelligence stack, providing full-stack infrastructure for frontier-scale AI post-training and deployment. The company has raised $150M from top investors and is mission-driven, focused on open-source AI and accelerating science.
Design, build, and evolve systems for distributed model training and batch inference at scale.
Develop workflows for experiment tracking, model evaluation, and registry management.
Optimize training and inference performance across GPU utilization, data loading, and distributed communication.
NOETIK is a frontier therapeutics company using AI to understand human biology and improve oncology outcomes, building foundation models on proprietary multimodal data. It fosters a collaborative, interdisciplinary culture focused on solving hard problems together.
Design, run, and analyse large-scale RL post-training experiments such as RLHF and RL from verifiable rewards.
Research and develop methods that improve out-of-distribution generalization, including reward design, task diversity, and regularization.
Build held-out evaluations to measure generalization and catch reward hacking, and turn successful research into production training recipes.
Cohere is a leading security-first enterprise AI company building cutting-edge foundation models and end-to-end products for businesses. We are a global team of researchers, engineers, and designers passionate about their craft, headquartered in Toronto with offices worldwide.
Distributed pretraining: Implement and optimize model-parallel training on heterogeneous GPUs under low-bandwidth, high-latency links.
Performance optimization: Apply techniques that reduce communication overhead while maintaining model convergence in challenging network environments.
Elasticity and fault tolerance: Build robust checkpointing and recovery so runs survive node churn as participants join and leave.
Pluralis Research is a decentralized AI research company developing Protocol Learning to train large models on consumer devices across the internet. The team is world-class and deeply technical, backed by tier-1 investors, with a remote-first culture.
Own the architectural evolution of the operator foundation model, designing transformer variants for spatial domains and scaling distributed training beyond 45TB datasets.
Architect trillion-voxel inference systems that balance memory, compute, and communication with production-grade stability.
Ship expanded operator capabilities into production, increasing simulation throughput by 100x across global, multi-entity deployments.
Vinci builds operator intelligence infrastructure that modern hardware programs rely on, with a single foundation model deployed across industries on realistic production workloads. They are a Series A company with 45TB+ of physics data, running billion-voxel inference inside Tier-1 semiconductor environments.