Top AI & Machine Learning Jobs

Principal Data Scientist partnering with cross-functional teams to solve product and business problems through quantitative analysis, experimentation, forecasting, and product metrics. The role develops hypotheses, evaluates opportunities, influences product roadmaps, identifies challenges, and communicates data-driven insights and recommendations to leadership.

Leads the development of an enterprise AI-driven model validation platform, agentic systems, and real-time monitoring capabilities. Manages AI scientists and engineers, defines product requirements and roadmaps, delivers cloud-native solutions on GCP, and partners with model risk, technology, and business stakeholders. Provides hands-on technical leadership across AI agent design, development, testing, validation, and productionization while fostering talent development and continuous improvement.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Build Onebrief’s AI Engineering Platform by architecting multi-agent systems, governance and policy engines, semantic context and memory infrastructure, evaluation frameworks, and self-healing observability loops. Rapidly prototype and deploy agentic tools to production, experiment with models and orchestration techniques, and collaborate intensely across disciplines. Candidates must be product builders, active agentic builders, strong communicators, and experienced in shipping reliable products.

Leads computer vision, machine learning, and tracking teams while translating AI strategy into roadmaps, standards, and deliverables. Manages managers, mentors technical staff, coordinates cross-disciplinary engineering efforts, owns schedule execution, and drives integration risk resolution. Establishes model evaluation and reproducibility practices, reviews code, develops prototypes, and supports architecture decisions for real-time perception systems.

Research intern supporting advanced analytics and new product development for revenue management. Responsibilities include preparing and analyzing data, identifying problems, designing and implementing solutions, researching forecasting, pricing, optimization, generative AI, and machine learning applications, presenting findings, and producing technical documentation. The role involves Python, SQL, Pandas, LLMs, RAG, and prototyping with tools such as LangChain and visualization frameworks.

Build AI workflows, agents, and customer-facing web experiences that accelerate website production and improve conversion. The role involves optimizing Contentful-based processes, configuring chat, enrichment, voice AI, and personalization tools, running experiments, establishing AI guardrails, monitoring performance, and training marketing teams on reusable AI systems. Collaboration spans Web Platform, CRO, SEO, product marketing, legal, privacy, and brand teams.

Leads the technical direction, architecture, and roadmap for agentic machine learning systems processing global trade data. Builds ingestion, document understanding, entity resolution, inference, evaluation, observability, and feedback systems. Adapts and post-trains LLMs, ships production AI agents, mentors engineers, sets technical standards, and partners with product, engineering, data science, and customers to deliver risk, compliance, and enforcement capabilities.

Design and deploy production-grade ML models and GenAI/LLM solutions to improve customer segmentation, churn prediction, LTV estimation, and automate enterprise workflows. Build cloud-native data science pipelines, measure impact via experiments, create executive dashboards, and mentor peers on MLOps and data storytelling.

Leads forward deployment of agentic AI systems within a business unit. Designs and delivers production LLM solutions, including integrations, RAG pipelines, prompt orchestration, multi-agent workflows, data engineering, and performance experiments. Measures ROI, improves data quality, mentors engineers, guides technical delivery, and communicates with business stakeholders. The role requires strong Python, cloud-native deployment, enterprise integrations, responsible AI, and data security expertise.