Applied AI Scientist: Build Production AI Solutions

Lumen

Honolulu (HI)

On-site

USD 111,000 - 185,000

Full time

7 days ago

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Job summary

Lumen is seeking a highly technical and execution-oriented Applied AI Scientist to design, develop, deploy, and optimize AI-powered solutions that solve meaningful business challenges. In this role, you will partner with business, product, engineering, and technology teams to identify opportunities, rapidly prototype solutions, and deliver production-ready AI capabilities.

You will combine expertise in machine learning, generative AI, software development, and experimentation to create scalable

Qualifications

3+ years of experience in applied AI, machine learning, data science, or a related field.
Experience developing and deploying production AI or machine learning solutions.
Strong expertise in machine learning, statistics, predictive modeling, experimentation, and analytics.
Experience building solutions utilizing LLMs, RAG architectures, vector databases, and modern AI frameworks.
Proficiency in Python and common AI/ML toolsets such as PyTorch, TensorFlow, Hugging Face, LangChain, MLflow, or similar technologies.
Experience working with cloud platforms and production software environments.
Strong problem-solving skills and the ability to communicate technical concepts to diverse stakeholders.
Experience working in cross-functional agile teams.

Responsibilities

Design, develop, and deploy AI and machine learning solutions from proof of concept through production.
Partner with business and product stakeholders to identify use cases, define objectives, and measure impact.
Build solutions leveraging machine learning, generative AI, retrieval-augmented generation (RAG), NLP, predictive analytics, and agentic workflows.
Develop and maintain evaluation frameworks to ensure solution quality, accuracy, reliability, and performance.
Collaborate closely with Engineering teams to operationalize AI solutions using MLOps and LLMOps best practices.
Contribute reusable code, tools, models, and frameworks that accelerate AI adoption across the enterprise.
Stay current on emerging AI technologies and recommend innovative approaches to business challenges.
Contribute to technical best practices and knowledge sharing across the team.