AI Operations Specialist

Contract: Full-time, Permanent Role We are looking for an AI Operations (AI Ops) Specialist who will act as the bridge between technical AI development and day-to-day business execution. You will deploy, manage, and scale AI tools and machine learning (ML) models to automate workflows, improve reliability, optimize IT operations, and increase overall company efficiency. You will work closely with AI and software engineers, roboticists, ITC, and business intelligence to ensure our AI framework is observable, secure, measurable, and continuously improving. The ideal candidate is hands‑on, pragmatic, and comfortable developing production environments and operational outcomes. Responsibilities

Drive automation and process optimization of internal workflows using AI tools. Operationalize AI solutions: deploy models and AI services into production with robust release processes. Build and maintain AI Ops pipelines (automated testing, versioning, rollback strategies). Implement monitoring and observability for AI systems: performance, drift, data quality and compliance, latency, errors, and cost. Own incident response and troubleshooting for AI services (root cause analysis, post‑mortems, preventative actions, planning improvements). Improve efficiency and scalability: resource planning, cost optimization, capacity management, and model serving performance. Ensure AI solutions follow security, privacy, and governance best practices (access controls, auditability, safe deployment patterns). Collaborate with robotics/deployment/operations/business teams to set standards for AI tools adoption (testing, validation, reproducibility).

Requirements

Master's degree in Engineering, Computer Science, Machine Learning or equivalent technical backgrounds. Ability to evaluate, select, and deploy AI tools/platforms based on defined internal KPIs, and to demonstrate measurable operational impact through structured tracking and reporting. Strong software fundamentals and practical coding skills in Python, plus knowledge of scripting/automation. Experience with modern deployment practices (e.g., Git-based workflows, automated testing, release management). Familiarity with containers and orchestration. Cloud or infrastructure familiarity (e.g., Azure/AWS/GCP, on-prem setups, or hybrid environments). Availability to travel nationally and internationally is expected. Exposure to compliance/privacy topics (e.g., GDPR, AI act), auditability, or security reviews for AI systems. Experience designing KPI frameworks for operational AI adoption (business impact metrics, efficiency measurements). Hands‑on experience with MLOps tooling such as MLflow. Deployment of AI tools on local computational resources.

We Offer

The chance to build and scale AI operations at a company where reliability and real‑world deployment matter. A collaborative environment with tight feedback loops between AI development, engineering, and business execution. The opportunity to contribute to the growth of a cutting‑edge deep tech company. A stimulating and informal work environment, working closely with highly skilled technical and research teams. Concrete opportunities for professional growth. Disclaimer We are proud to be an Equal Opportunity Employer. We evaluate all qualified applicants solely on the basis of merit and business needs, without distinction or discrimination based on gender, race, color, ethnic or social origin, age, religion, sexual orientation, gender identity, disability, or any other characteristic protected by law. #J-18808-Ljbffr