Top AI & Machine Learning Jobs

Lead end-to-end strategy, roadmap, technical execution, and measurement for Answer Engine Optimization (AEO). Own retrieval, indexing, bot access, measurement systems, and productization; drive cross-functional engineering, market intelligence, and executive communications to optimize visibility and commercial outcomes with frontier LLMs and agentic search.

Lead strategy and roadmap for AI-powered learning products, drive high-priority AI initiatives from concept to scale, partner cross-functionally to deliver responsible AI solutions, define success metrics and experimentation frameworks, and advise leadership on AI trends and opportunities.

Design, build, and deploy machine learning solutions in distributed systems; collaborate with engineers and subject-matter experts; evaluate and improve models; ensure data security and compliance; communicate insights to stakeholders; mentor junior data scientists.

Perform data cleaning, exploratory analysis, and build/productionize ML and statistical models (including NLP) to generate business value for service and fluids-analysis domains. Collaborate with cross-functional teams, present findings to stakeholders, and work independently on analytics projects within an Agile environment.

Design, build, and productionize agentic AI systems including LLM orchestration, retrieval, and evaluation. Work across the ML lifecycle from experimentation to deployment and monitoring, leverage proprietary structured and unstructured financial data, and collaborate with data, product, design, and MLOps teams to deliver scalable, robust agentic solutions.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Lead and grow a team of data scientists for SoFi’s consumer finance businesses. Prioritize and deliver high-impact data science and ML projects, build data pipelines, deploy and monitor models in production, mentor engineers, recruit talent, and collaborate cross-functionally with product, engineering, finance, risk, and executives to drive data-informed business decisions.

Lead design and build of a scalable, multi-tenant AI/ML platform powering traditional ML, LLMs, and agentic systems. Own end-to-end architecture, production-grade backends, orchestration, LLMOps, vector DB integration, and cross-functional delivery while enforcing engineering standards, security, and observability.

The Data Scientist will analyze data to provide insights, partner with teams for metrics, develop models, and create accessible visualizations to influence product and program strategies.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.