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.

Builds and operates scalable data infrastructure including compute fleets, storage systems, and streaming platforms to support OpenAI's AI products, research, and analytics. Requires 4+ years in data or infrastructure engineering with expertise in Spark, Kafka, and distributed systems.

Develops APIs and optimizes large-scale ML model inference using Python, Rust, C++, PyTorch, and CUDA. Benchmarks performance, improves reliability, and implements LLM optimizations on GPU architectures.

Develops compiler algorithms and optimization passes to lower and optimize deep learning and high-performance computing workloads for Quadric’s edge-focused neural processing architecture. Requires advanced computer science education, eight or more years of industry experience, and expertise in optimization, graphs, and machine-learning algorithms.

Develops and deploys state-of-the-art ML models for AI music generation, owning full research projects from data engineering to evaluation. Requires 5+ years training large generative models like LLMs/diffusion with distributed PyTorch.

Designs and deploys AI-driven agentic systems for retrieval, code generation evaluation, and agent backend architecture. Requires 2+ years AI/ML experience with LLMs, Bachelor's or Master's in CS/AI, and ability to prototype innovative solutions onsite in San Francisco.

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.

Leads development and deployment of ML models for NLP, retrieval, ranking, reasoning, dialog, and code-generation systems. Requires Master's/PhD, production ML experience, deep NLP expertise, Python proficiency, and MLOps knowledge in a fast-paced startup.

Software Engineer optimizes ML model inference performance using techniques like quantization and speculative decoding. Requires backend experience with PyTorch, TensorRT, CUDA, and deep GPU knowledge for LLMs.

Develop and deploy retrieval and search algorithms for OpenAI's API and ChatGPT, collaborating with research teams on production systems for millions of users. Requires experience with ML systems, vector databases, and large-scale search.

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.

Develops and optimizes deep neural networks for Quadric's GPNPU architecture, focusing on algorithmic lowering, graph-based execution, and performance extraction. Requires MS/PhD, 8+ years experience in optimization, ML algorithms, and graphs.

Develops alignment algorithms, data pipelines, and sampling methods to optimize post-training AI models for performance and efficiency. Requires PhD or equivalent, ML expertise including reinforcement learning and transformers, and production code experience.

Product Analyst conducts quantitative analysis for sports, media, and marketing products, developing KPIs, analyzing data with SQL/Python, and providing insights to business and client teams. Requires 1-3 years analytics experience and strong communication skills.

Build, deploy, and maintain scalable speech recognition pipelines, while experimenting with model architectures and modern ASR techniques. Requires 2+ years of experience, strong machine-learning fundamentals, Python and PyTorch expertise, and a bachelor's degree.

Leads ML performance optimization for training and inference platforms in autonomous driving, collaborating across teams to enhance efficiency using PyTorch, TensorRT, and profiling tools. Requires strong Python/C++ skills, GPU expertise, and 4+ years in large-scale ML platforms; leads engineering team.

Build and manage data pipelines and canonical datasets for product metrics, safety systems, and business decisions. Collaborate with cross-functional teams including Data Science and Research; requires 3+ years data engineering experience with Spark, ETL tools, and distributed systems.

Builds and leads data acquisition systems including web crawling, ingestion, and scalable distributed processing for model training. Requires 4+ years experience, expertise in Kubernetes and large-scale data systems, and BS/MS/PhD in Computer Science.

Builds ETL pipelines and Python scripts to ingest, transform, and manage customer R&D datasets for a scientific web platform. Targets recent graduates with Python scripting, data manipulation experience, and CS coursework.

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.

As a Software Engineer specializing in Mapping and Localization, you will design and implement state-of-the-art systems for autonomous vehicles and mobile robots. This role involves building scalable solutions, fusing live data with maps, and continuously improving system performance using data-driven methods.

Staff Data Scientist evaluates behavior in autonomous driving systems by analyzing large-scale fleet and simulation data, developing ML algorithms for feature engineering and model optimization, and ensuring safety through rigorous testing. Requires Master's/PhD and 8+ years experience in data science with Python and ML 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.

Develop, deploy, and optimize production-scale ML models using deep learning frameworks like PyTorch/TensorFlow. Requires 5+ years experience, expertise in Python, distributed systems, and focus areas like computer vision or NLP.

Develops, deploys, and optimizes state-of-the-art ML models for production at scale, handling terabyte datasets and neural networks. Requires 8+ years experience, expertise in PyTorch/TensorFlow/Python, and focus in CV/NLP.

Develops and deploys perception algorithms for autonomous driving, focusing on object detection, sensor fusion, localization, and tracking using LiDAR, cameras, and radar. Requires Master's degree and 4+ years non-academic experience in computer vision.

Builds product workflows and agentic systems using language models for research tasks like evidence synthesis and experiment planning. Combines ML fluency with strong software engineering to create reliable, trustworthy AI tools for scientific decision-making.

Develops, trains, deploys, and optimizes deep learning models for production use cases involving large datasets. Requires 1-2 years ML experience, Python proficiency, and familiarity with ML frameworks like TensorFlow or PyTorch.

Build and refine data models using SQL and Python to enable self-service analytics, analyze customer data, and collaborate with cross-functional teams. Requires 5+ years experience in analytics/data roles and strong data modeling skills.

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.