Top AI & Machine Learning Jobs

Conduct an applied AI research project with mentorship, covering agent evaluation, reasoning, tool use, policy adherence, post-training, and multimodal or voice models. Design rigorous experiments, analyze proprietary text and audio datasets, develop benchmarks, write and submit research papers, and collaborate with engineers to translate findings into production improvements.

Lead and mentor an AI agent engineering team developing scalable, secure HR and Finance AI solutions. Drive technical strategy, project delivery, platform integration, and adoption of LLMs, RAG, and orchestration frameworks such as LangGraph. Partner with product, data science, architecture, vendors, and open-source communities while ensuring privacy, security, compliance, testing, monitoring, reliability, and performance.

Summer 2027 data science internship supporting Northrop Grumman’s Product Support organization. The intern will develop machine learning and predictive analytics solutions, build statistical tools, model complex data, write maintainable code, contribute to testing and documentation, implement CI/CD practices, and optimize algorithms and data workflows in an on-premise environment.

Analyze neural and behavioral research data end to end, including statistical design, signal quality, preprocessing, quality control, decoding models, pose and kinematic analysis, and reproducible pipelines. The role supports study design, closed-loop sessions, publications, and collaboration with scientific and software teams to translate research methods into reliable workflows.

Build and operate supply chain data pipelines, models, integrations, quality controls, and dashboards supporting procurement, inventory, logistics, suppliers, and project analytics. Partner with analysts and business teams to enable forecasting, planning, scorecards, KPI tracking, and data governance. Contribute to cloud data architecture, engineering standards, tooling implementations, and productionizing analytics models across AI infrastructure and capital-intensive supply chain operations.

Supports oncology research through clinical, genomic, sociodemographic, behavioral, wearable, and patient-reported data processing and analysis. Assists with data cleaning, harmonization, integration, visualization, AI risk algorithms, dashboards, digital health tools, and supportive care applications. Participates in supervised research, data pipeline reviews, troubleshooting, and mentor meetings.

Build and operate full-stack features for an AI-powered consulting platform. Responsibilities include frontend and backend development, data pipelines, APIs, LLM-based extraction, retrieval, chat, content generation, AI coding workflows, testing, evaluations, and quality checks. The role owns platform areas end to end, collaborates with consultants, product, and design, and translates expert judgment into reliable AI-assisted functionality.

Build and ship production AI systems for enterprise portfolio and planning workflows. Develop anomaly and signal detection, LLM-powered insight synthesis, natural-language planning rule translation, evaluation frameworks, and MCP tools. Partner with external AI providers initially, then establish internal standards for prompt design, model selection, agent architecture, reliability, and evaluation. Collaborate closely with product, design, and domain engineering teams.

Leads global engineering teams developing Private AI products and services, integrating with vSphere, NSX, and vSAN. Owns platform reliability, security, lifecycle management, SDLC execution, and day-two operations. Defines Broadcom’s upstream contribution strategy and represents the company in the Kubernetes and CNCF ecosystems. Requires deep Kubernetes expertise, significant open-source influence, distributed-systems experience, and global engineering leadership.

Lead AI/ML initiatives for Air Force condition-based maintenance, from predictive model development through production deployment. Architect data pipelines, develop machine learning, deep learning, NLP, and generative AI solutions, and build knowledge graph capabilities. Provide technical leadership, integrate models into applications and workflows, and monitor data quality, model performance, drift, and bias. Collaborate with engineering, cloud, software, and product teams while supporting defense aviation logistics and sustainment missions.