Top AI & Machine Learning Jobs

Supports data science solutions for natural gas utility operations through exploratory analysis, feature engineering, statistical and machine learning model development, forecasting, optimization, data validation, visualization, and documentation. The intern will work with operational, weather, telemetry, billing, and usage data; contribute to Microsoft Fabric pipelines; complete an assigned project; and present findings to data teams and leadership.

Build and own AI-powered product features end to end in a Seed-stage startup. Translate product needs into scalable solutions, prototype rapidly, integrate evolving AI models and frameworks, and maintain production quality. Contribute across frontend, backend, and infrastructure while shaping technical direction through hands-on engineering rather than people management. The role requires strong ownership, customer focus, communication, and comfort with ambiguity.

Lead architecture across engineering teams and design AI-augmented capabilities for a regulated payment-integrity platform. Map the current architecture, create AI and platform roadmaps, establish integration and security standards, build reusable software assets, and ship an extensible AI MVP. Define governance, evaluation, and bias-testing methods while advising sales, operations, customers, and executives on practical AI adoption.

Leads the identification, design, evaluation, integration, implementation, and adoption of AI solutions across the firm and portfolio companies. Partners with business, Technology, and Legal teams to apply generative AI, intelligent agents, enterprise search, workflow automation, and other technologies to business processes. Establishes reusable implementation playbooks, incorporates security and responsible AI controls, measures business impact, and drives continuous improvement.

Develop and execute go-to-market strategy for AI products: define positioning and messaging, conduct market and competitive analysis, enable sales, coordinate launches, gather customer insights, and measure product performance.

Conduct software research and development involving C, Python, machine learning algorithms, and advanced algorithmic solutions. Research, prototype, implement, validate, and improve machine learning concepts through software. Analyze complex technical problems, collaborate with engineering and research teams, and document technical findings and implementations.

Translate business objectives into actionable data analysis, analyze large datasets, apply statistical and machine learning methods, and clearly communicate findings to technical and non-technical audiences. The role requires Hadoop ecosystem expertise, Python scripting, strong statistical knowledge, sampling and analytical skills, and business domain experience in retail, enterprise mobility, or healthcare.

Build production-quality AI applications using Python and existing large language models. Design multi-agent and multi-step workflows with prompt chaining, tool use, and orchestration; engineer and evaluate prompts; integrate AI into RESTful APIs and microservices; and deploy solutions on AWS. Preferred work includes RAG pipelines, vector databases, observability, exploratory data analysis, and MLOps/LLMOps practices.

Develop and maintain the U.S. Census Bureau’s LLM Autocoder using Python, LLMs, prompt engineering, text classification, structured outputs, and testing. Build survey-specific pilots, troubleshoot production issues, evaluate model changes, and collaborate with data scientists and MLOps engineers on AWS deployment, rollback, and verification. Maintain documentation and support government handoff while meeting Census security and operational requirements.

Data Science Interns analyze and clean large datasets, create reports, dashboards, and visualizations, and support predictive modeling, statistical analysis, and machine learning initiatives. They identify trends, validate data quality, collaborate with business partners, and present insights and recommendations. The role offers hands-on experience with business data, mentoring, and analytics projects while requiring strong analytical, communication, and organizational skills.