Senior AI/ML Engineer - Lead AI Solutions & Integrations

JOB OPPORTUNITY

Title: AI/ML Enginee

rFull Tim

eLocation: Onsite 4 days a week in Mayfield Heights, OH 44124 (Relocation expenses paid

)
Top Skill

s:• Pyth

on• Gen AI. LLM, RAG. Agentic AI nice to hav

e.• Azure, but will accept AWS or GC

P.• ML nice to hav

e.
Summ

aryThe Senior AI / ML Engineer will lead the design, delivery, and operations of machine learning and generative AI solutions across our digital products and platforms. This senior role balances hands-on engineering, architectural leadership, and cross-functional collaboration to drive measurable business outcomes, while ensuring responsible AI practices and robust production reliability. This role reports to the Enterprise Digital and IT Lead and is recognized as a subject matter expert (SME) in AI solutions, enterprise integrations and modern software development practices, operate autonomously, set technical standards, mentor others, and influence AI strategy across multiple teams and doma

ins
Qualificat

ions• 4-year University de

gree• Five or more years of experience in Information Techno

logy• Programming: Expert in Python and SQL; strong software engineering practices (testing, patterns, performan

ce).• Classical ML: supervised/unsupervised learning, model evaluation, feature engineering, time ser

ies.• Deep Learning: PyTorch or TensorFlow, transformers, CV/NLP pipeli

nes.• Generative AI: LLMs, RAG, fine-tuning, prompt design, evaluation metrics and guardra

ils.• Agentic AI: Practical experience with concepts such as tool-calling, reasoning loops, task planning or multi-agent orchestration (e.g., AutoGen, LangChain Agents, LangGr

aph)• Data processing: Spark/Databricks or equivalent; batch and streaming (e.g., Kaf

ka).• Storage: relational and NoSQL; data lakes; vector databases (e.g., FAISS, Pinecone, Weavia

te).• CI/CD (e.g., GitHub Actions, GitLab CI), containerization (Docker), orchestration (Kubernet

es).• Experiment tracking and model management (e.g., MLflow, Weights & Biases, D

VC).• Cloud: Proficiency with one major cloud (AWS, GCP, or Azure) for training and serving (e.g., SageMaker, Vertex AI, A

KS).• Security and Privacy: Experience handling sensitive data (PII), encryption, access controls, secure model serv

ing.• Search and retrieval: Elastic/OpenSearch, knowledge graphs, advanced RAG patte

rns.• Ethics and Compliance: Champions responsible AI and governa

nce.• Delivery: On-time, high-quality deployment of ML/LLM features into product

ion.• Assess current AI/ML assets, data pipelines, and platform maturity; identify quick wins and strategic g