Digital & IT Senior Analyst - AI/ML Engineer

Parker Hannifin Corporation; Mayfield Heights (OH); On-site; USD 120,000 - 150,000; Full time

Job summary

Parker Hannifin Corporation in Mayfield Heights, Ohio seeks a Senior AI / ML Engineer to lead the design and implementation of machine learning solutions across digital products. Responsibilities include overseeing AI initiatives from inception to deployment, mentoring engineers, and ensuring responsible AI practices while delivering high-quality solutions in production. Candidates should have a 4-year degree and significant experience in IT with a strong focus on Python, deep learning frameworks, and cloud services.

Qualifications

• Five or more years of experience in Information Technology.
• Classical ML: supervised/unsupervised learning, model evaluation.
• Experience handling sensitive data (PII) for security and privacy.

Responsibilities

• Own AI initiatives from problem framing through deployment and monitoring.
• Design, train, and optimize models for NLP/LLM use cases.
• Build reliable ML infrastructure and services with CI/CD.

Skills

Expert in Python

Strong software engineering practices

Deep Learning

Generative AI knowledge

Data processing with Spark

Education

4-year University degree

Tools

PyTorch

TensorFlow

Docker

Kubernetes

AWS

Job description

Position Summary

Our Digital Technology organization builds data- and AI-powered experiences for internal users and customers. The team spans data engineering, ML engineering, product, and platform operations, working end-to-end from data pipelines through model deployment, monitoring, and continuous improvement. The 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, operating autonomously, setting technical standards, mentoring others, and influencing AI strategy across multiple teams and domains.

Responsibilities

• Own AI initiatives from problem framing through deployment and monitoring (data, modeling, evaluation, serving, and iteration).
• Design, train, and optimize models for NLP/LLM use cases (e.g., RAG pipelines, fine‑tuning, prompt engineering, safety and guardrails).
• Build reliable ML infrastructure and services (APIs, containers, Kubernetes), integrating CI/CD and automated testing.
• Establish evaluation frameworks (offline metrics, online A/B tests, human‑in‑the‑loop reviews) with clear success criteria.
• Implement observability for models (drift detection, performance/SLOs, error analysis, data quality checks).
• Ensure security, privacy, and compliance (PII handling, model safety, prompt‑injection defenses, auditability).
• Partner with product to scope roadmaps, estimate effort, and align technical plans with business outcomes.
• Mentor engineers, contribute to architecture decisions, and champion best practices across the AI/ML stack.

Qualifications

• 4‑year University degree
• Five or more years of experience in Information Technology
• Programming: Expert in Python and SQL; strong software engineering practices (testing, patterns, performance).
• Classical ML: supervised/unsupervised learning, model evaluation, feature engineering, time series.
• Deep Learning: PyTorch or TensorFlow, transformers, CV/NLP pipelines.
• Generative AI: LLMs, RAG, fine‑tuning, prompt design, evaluation metrics and guardrails.
• Agentic AI: Practical experience with concepts such as tool‑calling, reasoning loops, task planning or multi‑agent orchestration (e.g., AutoGen, LangChain Agents, LangGraph)
• Data processing: Spark/Databricks or equivalent; batch and streaming (e.g., Kafka).
• Storage: relational and NoSQL; data lakes; vector databases (e.g., FAISS, Pinecone, Weaviate).
• CI/CD (e.g., GitHub Actions, GitLab CI), containerization (Docker), orchestration (Kubernetes).
• Experiment tracking and model management (e.g., MLflow, Weights & Biases, DVC).
• Cloud: Proficiency with one major cloud (AWS, GCP, or Azure) for training and serving (e.g., SageMaker, Vertex AI, AKS).
• Security and Privacy: Experience handling sensitive data (PII), encryption, access controls, secure model serving.
• Search and retrieval: Elastic/OpenSearch, knowledge graphs, advanced RAG patterns.
• Ethics and Compliance: Champions responsible AI and governance.
• Delivery: On‑time, high‑quality deployment of ML/LLM features into production.
• Assess current AI/ML assets, data pipelines, and platform maturity; identify quick wins and strategic gaps.

Equal Employment Opportunity

Parker is an Equal Opportunity and Affiliation Employer. Parker is committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job related reasons regardless of race, ethnicity, color, religion, sex, sexual orientation, age, national origin, disability, gender identity, genetic information, veteran status, or any other status protected by law. However, U.S. Citizenship, Permanent Residency or other appropriate status is required for certain positions, in accord with U.S. import & export regulations.
(Minority / Female / Disability / Veteran / VEVRAA Federal Contractor)