Top AI & Machine Learning Jobs

Staff-level ML and agent systems engineer responsible for production model lifecycles, multi-step agentic systems, evaluations, retrieval and context engineering, and model cost and latency optimization. The role owns technical direction for Code Understanding products, improves model and agent quality, establishes evaluation and monitoring standards, mentors engineers, collaborates with customers, and delivers reliable AI-powered developer experiences at enterprise scale.

Summer data science internship involving development and project work with JavaScript, HTML/CSS, SQL Server, VBA, Python/Django, and Git-based Azure DevOps workflows. Interns must work full-time for 12 weeks at a Houston-area site and be pursuing a relevant bachelor's degree with at least a 3.0 GPA. The program includes networking, housing eligibility, benefits, and potential full-time conversion.

Develop machine learning and AI methods for cybersecurity products using large-scale network telemetry. Analyze anomalies and malicious behavior, engineer features, evaluate models on imbalanced and incomplete data, establish monitoring metrics, and conduct error analysis. Collaborate with threat researchers and software engineers to productionize solutions, research emerging techniques, communicate findings, document methodologies, and mentor data scientists.

Design and deploy deep learning systems for search ranking, personalized recommendations, geospatial search, and pickup-point selection. Translate business goals into ML objectives, lead offline and online evaluation, conduct A/B tests, and partner with engineering on production model serving and latency optimization. Own the production ML lifecycle, including monitoring, drift detection, retraining pipelines, and quality management across international markets.

The AI Solutions Analyst identifies business opportunities for generative AI and process automation, translates requirements into scalable solutions, develops prompts and workflows, monitors AI quality, supports testing and adoption, creates documentation and training, and measures business impact. The role partners across business and IT teams and serves as an enterprise AI productivity tools subject matter expert.

Develops advanced analytics for national security using large, disparate datasets. Responsibilities include designing data exploitation methods, researching sponsor inquiries, developing custom searches, applying classification, regression, clustering, and anomaly detection algorithms, and supporting threat hunting and malicious-activity detection. The role also involves statistical analysis, data visualization for nontechnical audiences, and prototyping data engineering pipelines.

Lead computational analysis for research on intrinsically disordered proteins and regions. Develop reproducible pipelines, integrate HDX-MS, interactomics, cryo-EM, and molecular-dynamics datasets, apply statistical and machine-learning methods, create visualization tools, support experimental design, and collaborate with structural biology, proteomics, and computational modeling teams. Contribute to publications, technical reports, and open computational resources.

Build Way’s data and intelligence layer across pricing, merchandising, personalization, forecasting, recommendations, and automation. Own data foundations, metrics, models, experiments, and production-ready datasets while partnering with Product and Engineering. Identify high-impact opportunities, ship measurable solutions, and establish rigorous, responsible data practices in a fast-moving startup environment.

Architect and deploy Shipt’s foundational agentic AI platform for real-time routing, pay, and fulfillment coverage. Build autonomous reasoning loops, tool-binding frameworks, multi-agent orchestration, and high-throughput microservice integrations. Lead technical discussions, mentor engineers, manage production services, optimize agent costs, implement lifecycle governance and RBAC, and develop evaluation and monitoring strategies for reliable, compliant, fiscally responsible AI workflows.

Designs, builds, deploys, and improves AI solutions and agentic workflows across the company. Responsibilities include evaluating AI tools, defining architecture, integrating systems, implementing guardrails, monitoring performance, documenting solutions, supporting training, and partnering with IT and Security on SOC 2 compliance. The role owns the technical AI roadmap and release readiness while enabling staff to adopt AI safely and effectively.