Top AI & Machine Learning Jobs

Own product and business analytics across experimentation, causal inference, instrumentation, KPI reporting, pricing, advertising, subscriptions, and conversion. Design experiments, analyze event-level consumer data, partner with engineers on telemetry, and communicate recommendations using statistical rigor. The role also supports thought leadership, manages an independent analytics roadmap, and informs product and business strategy.

First engineering hire responsible for defining the technical foundation, selecting the technology stack, and building Orpex’s AI workforce infrastructure. The role involves shipping production agent systems, owning full-stack development and deployment, engaging users, iterating on products, managing infrastructure and UI, and helping hire future engineers.

Data Science Interns will improve production machine learning models for lifetime value, unit economics, and forecasting. They will audit models, engineer features, validate predictions, design A/B tests with Product, Marketing, and Sales, and interpret results. The role requires rigorous statistical inference, strong Python and SQL skills, clear communication, and a willingness to investigate model and data issues. Interns will work with Python, dbt, Dagster, Redshift, Athena, Cube, and Superset under mentorship.

Build and deploy AI-powered tools, workflows, applications, scripts, and integrations for WithCoverage’s Growth team. Partner with Product on implementation, testing, debugging, deployment, and iteration. Join sales and prospect conversations as a technical expert, explain AI concepts to nontechnical operators, demonstrate practical applications, and develop prototypes based on customer workflows. Document solutions, improve reliability, and communicate technical tradeoffs to Product and Engineering.

Build and execute AI-powered workflows for scripted content, leading projects from concept through delivery. Design scalable production pipelines, identify AI integration opportunities, collaborate with R&D and technical teams, and oversee field, post-production, and delivery operations. Manage cross-functional teams, vendors, and production partners while solving risks and adapting processes in a fast-moving environment.

Manages data-centric operations research and analytical programs supporting national security and space defense. Leads fact-based studies, requirements analysis, system modeling, data fusion technology development, project execution, resource allocation, and delivery of decision-support solutions to senior Department of Defense leaders. Mentors multidisciplinary teams and oversees complex systems-of-systems and enterprise architecture efforts.

Conduct applied AI safety research using white-box methods such as activation explainers, steering, attribution, and model-internal interventions. Evaluate methods on realistic, large-scale models and agentic coding tasks, develop practical monitors and interventions, publish findings, propose research directions, and engage with researchers, frontier AI developers, governments, and the broader AI alignment community.

Work with strategic enterprise customers to identify high-value AI opportunities, design and prototype AI-powered procurement solutions, demonstrate business value, and drive implementation, adoption, and measurable outcomes. The role combines customer workshops, solution architecture, stakeholder presentations, automation, and domain expertise across procurement, finance, and supply chain.

Build statistical and machine learning models that improve content discovery, user engagement, and retention. Apply causal inference, experimental design, and A/B testing to measure product impact and validate changes. Collaborate with ML engineers to deploy models, translate analysis into product decisions, and develop features using text, multimodal embeddings, and GenAI. Analyze large-scale data and recommender systems to drive measurable improvements in a consumer product serving millions of users.

Build Preql’s core agentic AI workflows for financial data cleaning and transformation. Responsibilities include developing LLM-powered data pipelines, conversational interfaces, audit-ready transformation engines, APIs, financial data integrations, and web-based workflow builders. The role owns the full stack, collaborates directly with enterprise customers, and takes the product from proof of concept to MVP while ensuring data lineage, reproducibility, and compliance.