Data and AI Engineer

The Data and AI Engineer will develop data, analytics, and artificial-intelligence solutions to help engineering teams identify trends, investigate product issues, improve decision-making, and accelerate technical problem solving. This role combines data engineering, statistical analysis, machine learning, software development, and technical communication, working with engineering and business stakeholders to transform complex, multi-source information into reliable datasets, useful analytical models, and clear technical insights.

Key Responsibilities:

• Collect, integrate, and organize structured and unstructured data from approved enterprise sources.
• Build repeatable workflows for data ingestion, transformation, validation, and quality monitoring.
• Clean, normalize, and prepare data for analytics, reporting, and machine-learning applications.
• Identify missing, inconsistent, duplicated, or anomalous records and document their impact.
• Maintain data lineage, version control, documentation, and reproducibility across analytical workflows.
• Apply statistical analysis, correlation techniques, and machine-learning methods to identify meaningful patterns and trends.
• Develop, test, and evaluate supervised, unsupervised, and hybrid analytical approaches.
• Define appropriate metrics and validation methods for model and workflow performance.
• Investigate false positives, false negatives, data-quality issues, model drift, and other analytical risks.
• Support the development of AI-enabled applications that combine data with approved technical or business knowledge.
• Evaluate large-language-model, retrieval, search, summarization, and knowledge-representation approaches where appropriate.
• Design prompts, evaluation criteria, and validation processes for AI-generated outputs.
• Improve the traceability, consistency, accuracy, and usability of AI-assisted results.
• Apply responsible-AI practices, including human review, access controls, data protection, and transparent documentation.
• Collaborate with software and platform engineers to move prototypes toward maintainable solutions.

Required Skills:

• 8+ years of experience working with Engineering Data, Analytics, and Artificial Intelligence.
• Experience in automotive, manufacturing, mobility, product engineering, quality, reliability, or operations analytics.
• Experience with telemetry, diagnostic, test, warranty, manufacturing, or other engineering-related data.
• Experience with cloud data platforms, distributed processing, or orchestration tools.
• Experience with large-language models, retrieval-augmented generation, embeddings, vector search, or knowledge graphs.
• Experience processing technical documents, source code, diagrams, or other semi-structured content.
• Experience developing dashboards, web applications, or self-service analytical tools.
• Experience with automated testing, CI/CD, data-quality frameworks, or model-regression suites.
• Professional experience with Python or another programming language used for data and analytics.
• Strong SQL skills and experience working with relational or analytical data platforms.
• Experience cleaning, transforming, joining, validating, and analyzing data from multiple sources.
• Familiarity with statistical methods, machine-learning concepts, and model evaluation.
• Experience with APIs, notebooks, cloud platforms, data pipelines, or analytical applications.
• Ability to understand technical documentation and collaborate with subject-matter experts.
• Strong written and verbal communication skills.
• Ability to work independently while contributing effectively to a cross-functional team.