AI Engineer

MSA Safety is building an AI Platform and is hiring an AI Engineer to design, build, and scale AI-enabled applications in a hybrid setup from Cranberry Township, PA.

Responsibilities

• Design and build AI-enabled applications and services for intelligent search, agentic workflows, and artifact generation
• Develop and orchestrate agentic systems that include tool use, multi-step reasoning, and evaluation loops informed by real-world feedback
• Deploy, monitor, and continuously improve models and AI services on AWS
• Collaborate with stakeholders across MSA business functions to translate real needs into tools for productive day-to-day use
• Participate in architectural discussions and support technical decision-making across the team
• Produce clean, maintainable, well-documented code and follow strong engineering practices including Git, code review, CI/CD, and testing

Requirements

• Bachelor’s Degree in AI Engineering, Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative discipline
• Experience building AI-enabled applications, ideally with agentic workflows, tool orchestration, and evaluation
• MLOps experience, including model deployment, monitoring, and evaluation in a cloud environment (AWS preferred)
• Proficiency in Python; TypeScript is a plus
• Working experience with at least one major ML framework: PyTorch or TensorFlow
• Strong understanding of transformer-based models, including multimodal architectures
• Familiarity with parameter-efficient fine-tuning such as LoRA and QLoRA, plus model optimization techniques including quantization, pruning, and distillation
• Understanding of end-to-end software systems across the stack and in the cloud, including containers, serverless functions, databases, and observability/telemetry
• Solid software engineering fundamentals with a history of clean, well-tested code
• Ability to adapt at a fast pace, with curiosity to learn new tools and frameworks as the AI ecosystem evolves
• Excellent communication skills, able to explain complex technical concepts to technical and non-technical stakeholders

Technologies

• Python, TypeScript, PyTorch, TensorFlow
• LoRA, QLoRA, quantization, pruning, distillation
• AWS, containers, serverless functions, databases, observability/telemetry
• Git, CI/CD, Hugging Face
• AWS Bedrock, Bedrock AgentCore, Strands
• SAP, Salesforce, SQL, ETL
• Vision Transformers, CNNs

Career Levels

• Level I: 0-1 years of experience
• Level II: 1-3 years of experience
• Senior: 3-5 years of experience

Preferred Education and Experience

• Master’s Degree
• Experience with open-source models via Hugging Face and managed services such as AWS Bedrock and Bedrock AgentCore, plus agent SDKs like Strands
• Experience working with enterprise ERP and CRM systems including SAP and Salesforce
• Experience delivering in an agile development environment
• Experience with Vision Transformers and/or CNNs
• Familiarity with SQL, ETL, and working with large datasets