ML Research Engineer trains foundational embedding models for web search, designs novel transformer architectures, creates datasets and evals, and beats state-of-the-art performance. Requires graduate-level ML expertise and ability to implement transformers in PyTorch.

Develops embedding models and retrieval systems to enable frontier AI models to access relevant information dynamically. Requires deep expertise in representation learning, vector retrieval, and transformer LLMs, with experience scaling ML systems.

Conducts research in mechanistic interpretability to understand deep network representations and enhance AI safety. Requires PhD or equivalent in ML/CS, 2+ years research engineering with Python, and passion for safe AGI.

Advances AI capabilities through cutting-edge reinforcement learning research, training intelligent agents for models like o1 and o3. Requires RL research background, strong coding skills, and ability to iterate quickly in a fast-paced environment.

Designs and tests zero-knowledge proof systems for biometric likeness verification in privacy-focused identity solutions. Requires expertise in zk-SNARKs/STARKs, cryptography, and prototyping tools like Circom and Semaphore.

Builds ambitious RL environments and evaluation systems to measure and steer frontier AI models toward safe AGI. Requires strong ML research engineering, statistical skills, and red-teaming mindset for end-to-end project ownership in fast-paced setting.

Builds advanced AI systems using massive-scale distributed machine learning to achieve breakthrough performance. Requires strong programming skills and experience with large distributed systems.

We are seeking full-time researchers to develop and analyze learning algorithms for a system that represents domain knowledge as modular probabilistic models. The role involves theoretical problems with immediate implementation applicability in finance and scientific research.

Develop machine-learning models and systematic trading strategies from large financial datasets, conducting quantitative-finance research and simulations. The role requires a STEM degree, Python proficiency, strong problem-solving skills, and interest or experience in alpha research.

Develops advanced AI agents for healthcare revenue recovery, focusing on human-like conversational AI, model improvements, LLM orchestration, and evaluation frameworks to handle insurance interactions and billing tasks.

Research Engineer working on frontier audio AI models, including training, post-training, data curation, architectural improvements, and rigorous evaluation. Requires at least 3 years of AI experience and evidence of solving challenging machine learning problems through projects or research.

Develops computational operators to enable LLMs to perform transparent, verifiable reasoning over thousands of iterations on knowledge states like scientific papers. Requires LLM experience, reasoning intuitions, and strong software engineering skills.

Designs and develops cutting-edge multimodal AI systems integrating text, speech, and vision. Conducts research on representation learning using Python, JAX, PyTorch, TensorFlow, with expertise in distributed training and autoregressive models.

Designs and implements experiments for AI alignment research, focusing on scalable solutions for human intent following, risk evaluation, model robustness, and oversight methods in complex scenarios. Requires PhD-level research experience and strong ML engineering skills.

Designs, implements, and maintains complex AI/NLP models for the Verneek AI platform, focusing on fundamental research grounded in real-world applications. Requires MSc/PhD in AI/NLP, 4+ years Python/PyTorch experience, and strong AI fundamentals.

Leads end-to-end research initiatives in machine learning and large language models for conversational AI in housing and healthcare. Requires PhD in relevant field plus 5+ years post-PhD experience, strong ML expertise, and Python proficiency.

Researches and develops generative AI features, agentic architectures, and language-model solutions for Pigment’s planning platform. The role combines experimentation and benchmarking with production Python development and requires advanced academic training in computer science, mathematics, or a related field.

Conduct AI research on large-scale diffusion models for anime imagery and other modalities, moving experimental models rapidly into production. The role requires research experience, diffusion-model knowledge, and PyTorch proficiency, with on-site work in Tokyo or San Francisco.

Senior researcher leading AI safety initiatives, conducting cutting-edge research on RLHF, adversarial training, and robustness to make AI systems safer and more aligned. Requires 4+ years in AI safety, PhD in ML/CS, and deep learning expertise.

Applied Research Scientist develops computer vision and generative models for creative AI tools, collaborating cross-functionally to productionize research. Requires 4+ years in ML/CV/graphics, strong Python/C++/PyTorch skills, and experience mentoring researchers.

Leads Applied ML Research team focused on computer vision and foundation models for AI content creation and world simulation. Requires 5+ years research experience, 1+ year managing teams, and skills in productionizing ML research.

Develop machine-learning and statistical trading signals for liquid financial assets, analyzing large datasets and testing quantitative-finance hypotheses through simulations. The role requires a STEM degree, Python proficiency, strong problem-solving skills, and an interest in machine learning.

Leads research in machine learning, robotics, and AI for autonomous systems, including perception, modeling, and inference. Requires PhD in related field, real-world data experience, and publications in top conferences.