Internship focused on AI, ML, data science, software devops, signal and image processing, and mathematics.
Compensation
$22.60 Hourly
Maximum Rate
$47.95 Hourly
Responsibilities
Collaborate with a passionate team dedicated to creating cutting‑edge solutions that address national priorities and deliver real‑world impact
Contribute to exciting projects and apply your skills in areas such as Artificial Intelligence, Machine Learning, Data Science, Software DevOps, Signal and Image Processing, and Mathematics
Senior AI Engineer, Hivemind Learning & Development is a hands‑on individual contributor who will build the AI‑powered products, content systems, and measurement capabilities that help engineers learn Hivemind faster and apply it successfully.
Compensation
Pay within range listed + Bonus + Benefits + Equity
Responsibilities
Develop an AI‑powered training coach that helps people learn Hivemind concepts, products, and development workflows.
Create highly technical Hivemind training materials and hands‑on workshops for engineers and other technical learners.
Build prompt‑based tooling that generates workshops and supporting learning content from defined objectives, audiences, and source materials.
Create LLM‑based tooling that automates the ongoing upgrade and improvement of Hivemind training and educational materials.
Build AI tools and systems that enable, streamline, and automate Hivemind Learning & Development workflows.
Own the backlog for one or two AI or data use cases, run use‑case intake, act as daily interface between business sponsor and engineering and data teams, prepare governance submissions, define and track adoption and value KPIs, support vendor and platform evaluations.
Responsibilities
Own the backlog for one or two AI or data use cases
Run use‑case intake
Act as the daily interface between the business sponsor and the engineering and data teams
Lead technical vision and architecture for AI/ML solutions across AstraZeneca’s commercial landscape, guiding advanced AI from traditional ML to generative and agentic AI, while influencing multi-functional teams and ensuring production readiness.
Responsibilities
Define and drive technical vision, roadmap and architecture for AI capabilities
Provide hands‑on technical leadership to project teams
Lead design of multi‑agent systems and LLM applications
Establish evaluation standards and quality gates
Drive model optimization and cost/latency improvements
Requirements
Bachelor's degree in Computer Science or related quantitative field
Master's or PhD in machine learning, computer science or related field
Senior AI Engineer, Agentic Solutions & Workflows is a hands‑on technical role responsible for designing, building, testing, deploying, and optimizing AI‑powered agents, workflows, and automation solutions that transform how teams work.
Compensation
$145,000-$185,000
Responsibilities
Translate complex business processes into AI‑enabled workflows
Develop reusable agents, workflow components, prompts, and AI accelerators
Build solutions using enterprise AI platforms, large language models, APIs, retrieval‑augmented generation (RAG)
Collaborate with AI Architects to ensure solutions align with enterprise architecture
Partner with Commercial, Medical Affairs, Publications, Scientific Services, Strategy, Digital, and client teams to identify and scope high‑value AI use cases
Lead technical vision and architecture for AI systems in a senior individual-contributor role, guiding advanced AI across commercial, medical, and technology domains.
Responsibilities
Define and drive the technical vision, roadmap and architecture for traditional ML, Generative AI and agentic AI capabilities
Provide hands‑on technical leadership to project teams; set design direction, review architectures and code, and remove blockers on sophisticated problems
Lead the design of multi‑agent systems and LLM applications, including orchestration, tool use, memory, guardrails and human‑in‑the‑loop patterns
Establish standards for evaluation, including automated and human‑in‑the‑loop methods, benchmarking, and quality gates pre‑ and post‑release
Drive approaches to fine‑tuning, distillation and reinforcement learning to improve quality, cost and latency over off‑the‑shelf models
Requirements
Bachelor's degree in computer science, mathematics, statistics, engineering, physics, computational sciences or a related quantitative field
Nice to have: Master’s or PhD in machine learning, computer science or related field
Nice to have: reinforcement learning (RLHF, RLAIF)
Architect the AI orchestration layer for a conversational commerce platform that powers AskOle’s global football super app.
Responsibilities
Design and lead the architecture of a next‑generation conversational AI platform
Coordinate multiple large language models, specialized agents, retrieval systems, recommendation engines, and external APIs into a single seamless conversational experience
Define technical vision, establish architectural standards, evaluate emerging AI technologies
Mentor senior engineers and make long‑term decisions regarding LLM strategy, retrieval architecture, agent design, memory management, semantic search, vector databases, knowledge graphs, and AI evaluation frameworks
Ensure integration across the entire ecosystem while maintaining scalability, reliability, performance, and user experience
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