This position is located in the Greater Cleveland area.
If you are not local, please advise in your application if you are willing to relocate yourself to this area.
Unfortunately , we are unable to provide visa support at this time, you must be a US Citizen or GC Holder.
Employment Type: Full‑Time, Permanent
About the Role
We are expanding our digital technology capabilities and looking for a Senior AI / ML Engineer to help shape and deliver intelligent solutions across our enterprise. This role sits at the intersection of data engineering, machine learning, and modern software development, supporting the full lifecycle of AI systems—from early exploration through production deployment and ongoing optimization.
You will play a key role in building scalable ML and generative AI capabilities, guiding architectural decisions, and ensuring that our AI systems are secure, reliable, and aligned with responsible‑use principles. This position is ideal for someone who enjoys both hands‑on engineering and technical leadership, and who thrives in a collaborative, cross‑functional environment.
What You’ll Do
- Lead AI/ML projects from concept through production, including data preparation, model development, evaluation, deployment, and continuous improvement.
- Develop and refine models for natural language, generative AI, and retrieval‑augmented applications, including fine‑tuning, prompt design, and safety controls.
- Build and maintain the infrastructure required to run ML systems at scale—APIs, containers, orchestration, CI/CD pipelines, and automated testing frameworks.
- Create evaluation strategies that combine offline metrics, online experiments, and human‑review processes to validate model quality and business impact.
- Implement monitoring and observability for ML systems, including drift detection, performance tracking, and data quality safeguards.
- Ensure AI systems meet security, privacy, and compliance expectations, particularly around sensitive data and model safety.
- Work closely with product teams to define requirements, estimate effort, and translate business needs into technical solutions.
- Mentor engineers, contribute to architectural standards, and help shape best practices across the AI/ML ecosystem.
- Assess current AI/ML tools, pipelines, and platform maturity to identify opportunities for improvement and innovation.
What You Bring
- Bachelor’s degree in a technical field or equivalent experience.
- 5+ years of experience in software engineering, data science, ML engineering, or related fields.
- Strong programming skills in Python and SQL, with a solid foundation in software engineering principles.
- Experience with classical machine learning techniques, feature engineering, and model evaluation.
- Hands‑on experience with deep learning frameworks such as PyTorch or TensorFlow, and familiarity with NLP/CV pipelines.
- Practical experience with LLMs, generative AI, RAG architectures, fine‑tuning, and prompt optimization.
- Exposure to agent‑based AI frameworks or multi‑step reasoning systems (e.g., LangChain Agents, LangGraph, AutoGen).
- Proficiency with distributed data processing tools such as Spark or Databricks, and streaming technologies like Kafka.
- Experience working with relational, NoSQL, and vector databases.
- Familiarity with CI/CD tools, containerization (Docker), and orchestration (Kubernetes).
- Experience with experiment tracking and model lifecycle tools (MLflow, Weights & Biases, DVC, etc.).
- Strong cloud experience with at least one major provider (AWS, Azure, or GCP), including managed ML services.
- Understanding of secure data handling, encryption, access controls, and safe model deployment practices.
- Experience with search, retrieval, or knowledge‑based systems (Elastic, OpenSearch, vector search, knowledge graphs).
- Commitment to responsible AI, governance, and ethical deployment of machine learning systems.
- Proven ability to deliver high‑quality ML/LLM features into production environments.
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