Top AI & Machine Learning Jobs

As the first Data Scientist, you will build models and algorithms from scratch, impacting the company's success in optimizing insurance portfolios.

The role involves optimizing analog-aware software for neural networks, designing algorithms, improving software quality, and collaborating on hardware validation. Requires experience with complex algorithms and communication skills.

Open application inviting scientists, engineers, and operators to apply for roles at the intersection of quantum computing and AI. Applicants should provide an introduction, explain their interest, describe desired roles, share relevant work, and note availability for Ann Arbor or San Francisco offices. The company offers visa sponsorship, competitive compensation, equity, health benefits, and unlimited PTO. Applications are reviewed on a rolling basis for current or future fits.

Develop and productionize photogrammetry and radar image-formation pipelines for large-scale 3D reconstruction. Improve pipeline stages (bundle adjustment, dense matching, point clouds, geo-referencing), optimize storage and databases for 3D geospatial data, and contribute to data infrastructure, analytics, and delivery systems for satellite-derived products.

Lead the ML platform and infrastructure (data, evaluation, compute). Own roadmap, build and scale distributed engineering teams, partner with Research and Applied ML to prioritize work, remain technically hands-on, and report to the CTO.

Serve as the primary technical contact during implementation: run discovery, capture operational and data requirements, translate needs into specs for offshore model development, manage technical customer communication, identify and resolve risks, and partner with delivery/product teams to accelerate time to value.

As a Research Scientist at Phonic, you'll lead original research in voice AI, drive experimental design, and influence model development directly.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

Build and ship production agentic AI systems end-to-end: scope, develop, deploy, evaluate, and monitor LLM-driven features integrated into a marketplace. Own 0-to-1 projects, collaborate with sales and operations, improve inference, evaluation, and monitoring infrastructure, and develop scalable tools for matching, document understanding, and agentic workflows.

Work with engineers to design, implement, and deploy scalable inference solutions for top AI models. Implement and optimize models (Python, C++, CUDA, NCCL), monitor live services, develop features, fix bugs, participate in code reviews, and collaborate in agile teams.