Top AI & Machine Learning Jobs

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

As a Lead Machine Learning Engineer, you'll manage AI/ML projects, optimize models, enhance ad-serving platforms, and mentor junior engineers.

Drive AI/ML solution sales for cable, media, and entertainment clients by developing POCs, proposing solutions, advising customers, building roadmaps, coordinating offshore delivery teams, and performing data-driven analysis to identify business improvements and implementation plans.

Build and deploy AI-powered applications and agents for engineers and operators across the rocket manufacturing organization. Responsibilities include full-lifecycle software development, foundation-model integration, retrieval and vector search, evaluation, reliability, testing, continuous integration and deployment, and collaboration with users to define and iterate on solutions. The role uses modern AI, data, cloud, and platform technologies in manufacturing and physical-world environments.

Own product strategy and execution for either LLM-driven conversational infrastructure or high-throughput outbound communications and experimentation. Drive experiments, data-informed decisions, and build 0-to-1 systems that tune messaging and borrower experiences across chat, voice, email, and SMS while navigating legal, ethical, and financial constraints.

The AI/ML Engineer will design, build, and deploy machine learning systems, optimize workloads, and ensure scalability and compliance of the ITMS platform.

The Forward Deployed AI Engineer develops AI solutions using LLMs, collaborates with customers on their AI strategy, and executes high-stakes projects to solve real-world problems.

Lead evaluation and data strategy for advanced AI, vision, and perception systems. Define metrics, build evaluation frameworks, audit artifacts, prioritize fixes, and translate model behavior into product decisions and data-improvement loops to ensure production readiness and downstream usefulness.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Lead web and marketing analytics: define tracking specs, implement and validate scalable tracking, join web and game data, build dashboards and reports, deliver campaign-level insights, measure feature effectiveness, and partner with stakeholders to make data actionable.