Top AI & Machine Learning Jobs

Analyzes internal and external marketing, sales, customer, and product data to develop predictive models, forecasts, dashboards, and actionable business insights. Builds data pipelines and BigQuery queries, performs data preparation and experimentation, and communicates findings through visualization tools. Guides generative AI adoption, develops AI agents and workflow automations, supports data governance, and partners with cross-functional teams to improve decision-making and marketing operations.

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.

Designs and deploys agentic AI workflows and Python automation pipelines, integrates LLMs into production systems, conducts vulnerability analysis, develops intelligence tradecraft, analyzes technical data, and supports customer requests and outreach. The role spans the full development lifecycle and requires expertise in prompt engineering, model optimization, networking, open-source research, SIGINT systems, and production CNO capabilities.

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.

Leads enterprise architecture strategy for data and AI modernization across business domains. Responsibilities include standardizing metadata, designing semantic data models and ontologies, guiding enterprise architecture decisions, partnering with product, engineering, data, and AI teams, supporting analytics and AI use cases, contributing to AI model development, overseeing MLOps practices, reviewing AI-generated code, and influencing senior stakeholders through hands-on execution and strategic leadership.

Designs and integrates AI-enabled modernization solutions while establishing quality assurance frameworks for AI-generated code, skills, agents, and prototypes. Develops test plans, acceptance criteria, regression suites, automated testing, security scans, and quality gates. Collaborates with DevOps teams on reliable multi-agent workflows, validates prototypes for production readiness, and monitors accuracy, security, compliance, and data-sensitivity risks.

Supports the development and evaluation of bioinformatics pipelines and internal tools for precision oncology products. The intern will document technical processes, learn agile development practices, work with genomic and Next-Generation Sequencing results, and assist with harmonizing genomic data. The role is a full-time, 11-week, in-person internship in Baltimore, Maryland, designed for currently enrolled students in relevant degree programs.

Develop and improve Tower’s internal agentic harness for autonomous coding, model building, long-horizon tasks, memory management, and multi-agent orchestration. Integrate tools and MCP systems, support current LLMs, identify automation opportunities with quantitative teams, and ensure regulatory compliance and production isolation. The role requires software engineering, data science, or ML engineering experience and strong knowledge of agentic frameworks and distributed systems.

Develop analytics, automation, and compliance software using machine learning and data-driven methods. Responsibilities include exploratory data analysis, feature development, model evaluation, ML deployment and monitoring, data processing workflows, emerging AI technology research, and software development in Linux using Python, Java, or Scala. The role also requires collaboration with technical and mission stakeholders, documentation, and adherence to agency compliance standards.

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.