Top AI & Machine Learning Jobs

Leads architecture for scalable, reliable agent-based AI products. Partners with product, engineering, data science, clinical, and customer teams to translate needs into architectures, prototypes, technical recommendations, and delivery plans. Conducts technical discovery, engages early-stage customers, evaluates adoption barriers, and guides solutions from proof of concept to production. Requires strong architecture judgment, communication, and experience shipping large-scale AI systems, with healthcare, deep learning, or NLP experience preferred.

Leads the credit union’s enterprise AI and automation function, setting strategy, governance, operating models, roadmaps, and prioritization frameworks. Identifies and delivers AI, generative AI, RPA, and intelligent automation use cases while ensuring regulatory, risk, ethical, and data governance alignment. Partners with business and technology teams on solution selection, process improvement, adoption, training, vendor coordination, KPI tracking, and value realization. Builds and manages a high-performing team.

Develop and productionize ML models across the full stack, optimizing training and inference for GPUs, NPUs, and AI silicon. Build inference runtimes, MLOps pipelines, embedded system integrations, verification harnesses, and security-focused ML capabilities. Collaborate with hardware, RTL, firmware, and QA teams to deploy AI features under real-world latency, memory, power, and reliability constraints.

Develop and maintain AI applications and technical solutions, build tools for analyzing large-scale data, troubleshoot and test software, and create technical documentation and user support guides. The role collaborates with developers, staff, leadership, and engineering teams to solve complex customer problems. Candidates need an active Top Secret clearance, a bachelor’s degree, five or more years of relevant experience, object-oriented programming expertise, and proficiency with modern LLM tools.

Develop and maintain credit risk models for origination, behavioral risk, underwriting, and portfolio management across Latin America. Own the full modeling lifecycle, including feature engineering, validation, backtesting, monitoring, calibration, and implementation. Analyze large financial datasets using Python and SQL, monitor portfolio and model performance, address data quality and selection bias, and translate analytical findings into credit strategies. Collaborate with Risk, Data, Engineering, Finance, and Operations teams.

Build and operate production agentic AI systems embedded within business units. Identify high-value automation opportunities, integrate CRM and business application APIs, design orchestration and evaluation frameworks, deploy monitored workflows, and measure ROI. The role requires close collaboration with GMs, sales, operations, customer success, and field teams while contributing reusable AI engineering patterns to a shared library.

Build and improve generative AI applications using LLMs, RAG workflows, APIs, databases, and backend components. Write tests, debug failures, improve performance and reliability, and collaborate on integration, deployment, and monitoring. The role also involves connecting models to external data sources and supporting scalable, reliable AI systems.

Builds and deploys AI-enabled applications, machine learning models, data pipelines, APIs, and decision-support tools for aggregate and asphalt operations. The role optimizes plant automation, production efficiency, uptime, quality, pricing, sales processes, and costs using operational, equipment, quality, GIS, and sales data. It integrates AI with plant systems and legacy software, collaborates across operations and IT, and ensures responsible AI, cybersecurity compliance, documentation, and user adoption.

Entry-level role supporting a law firm's Structured Finance & Derivatives group by evaluating and implementing generative AI tools, developing prompts and AI-powered workflows, testing outputs, researching emerging technologies, and identifying automation opportunities in legal practice. The position collaborates closely with attorneys and technology professionals and is designed for a tech-savvy graduating senior or recent graduate interested in AI, law, finance, or legal technology.

Own Workhelix’s analytical engine end to end, including customer data integration, ETL, data modeling, AI opportunity assessments, predictive analyses, visualizations, and production deployment. Build Python and SQL systems running in cloud infrastructure, develop customer-specific analyses, create internal analytical tools, and shape the data science roadmap. Partner with engineers, strategists, executives, and customers while setting standards for analytical rigor and translating research into practical business decisions.