Top AI & Machine Learning Jobs

Designs and supports data science and engineering intelligence applications that analyze large, diverse datasets. Responsibilities include developing analytical methods, maintaining applications on EIDH clusters, troubleshooting and validating upgrades, supporting system startups, creating customer and account reports, training users, serving as a subject matter expert, and coordinating with customers, IT, analytics, development, product, and global support teams.

Leads 3M’s enterprise generative AI adoption strategy and AI employee experience. Owns product roadmaps, use-case prioritization, governance, executive engagement, AI champion communities, platform integration, adoption measurement, and value realization. Partners with business, technology, data, cybersecurity, legal, privacy, and executive teams to move AI solutions from pilots to secure, scalable production deployments and measurable business outcomes.

Build AI-native developer tooling, including context aggregation, MCPs, CLIs, skills, sub-agents, and integrations with engineering systems. Develop AI-assisted workflows for code generation, review, testing, documentation, refactoring, and incident management. Establish autonomous development agents, optimize model selection and AI costs, improve developer velocity, and define standards for AI-generated code. Own system design and delivery while partnering with platform, infrastructure, and application teams.

Supports strategic pricing through advanced analytics, pricing models, competitive intelligence, elasticity and profitability analysis. Builds Power BI and Tableau dashboards, automated reporting, KPI scorecards, and analytical frameworks. Maintains pricing systems, performs UAT, documents processes, improves workflows, and supports cross-functional analytics projects. Translates complex datasets into recommendations for pricing, sales, marketing, product, finance, IT, and leadership stakeholders.

Build and maintain conversational AI agents and sales intelligence data products for revenue, pipeline, bookings, discounting, and territory analytics. Integrate enterprise systems including Salesforce, Snowflake, Databricks, BigQuery, and SharePoint; develop semantic models, retrieval pipelines, vector indexes, and evaluation datasets. Partner with sales, finance, IT, and security teams to scope solutions, validate quality, support governance, document capabilities, and enable user adoption.

Designs and owns enterprise software and AI systems, including full-stack applications, offline-first mobile tools, data platforms, financial models, LLM applications, machine learning workflows, and integrations with enterprise systems. Responsibilities include architecture, data modeling, evaluation, production reliability, security, migrations, observability, risk mitigation, and mentoring. The role partners with operations, finance, HR, safety, and project teams to deliver auditable, scalable solutions.

Design and implement scalable offline and online machine learning infrastructure for search and recommendation. Own data logging, processing, quality, model training, batch and real-time pipelines, and online inference services handling billions of records and petabytes of data. Partner with data scientists, analysts, product managers, and engineering teams while researching technical solutions and mentoring engineers.

Design and deploy an AI-enabled readiness and predictive maintenance platform for U.S. Army weapon systems and equipment fleets. Build data pipelines integrating maintenance, supply chain, telemetry, and operational data; develop survival analysis, forecasting, and optimization models; create dashboards for military leaders, logisticians, and maintainers; and implement RAG-based conversational AI with source attribution. The role requires DoD logistics expertise, an active Secret or TS/SCI clearance, and experience with Palantir, Microsoft Power Platform, or Python and SQL stacks.

AI Engineer Interns will preprocess and analyze data, support machine learning model development and optimization, help deploy AI solutions, document experiments and workflows, and research emerging AI methods. The role requires collaboration with senior engineers and cross-functional AI team members. Interns will work on ecommerce technology problems in a hybrid, full-time summer internship in Lehi, Utah, with potential for a future full-time role or part-time extension.

Leads the design, development, and deployment of enterprise generative and conversational AI solutions. Builds Python APIs, RAG architectures, vector database integrations, and multi-agent workflows using AI orchestration frameworks. Establishes evaluation, monitoring, observability, and reliability practices for chatbot performance and business outcomes. Collaborates with product, engineering, and business stakeholders to evaluate emerging AI technologies and drive secure, scalable enterprise adoption.