Data & AI Engineering

Prepare, clean, reconstruct, and validate structured, semi-structured, and unstructured data from datasets, documents, reports, exports, PDFs, and scans.

Build reproducible workflows using Python, SQL, notebooks, and version control; troubleshoot issues, test assumptions, and identify data-quality concerns early.

Support text extraction, classification, summarization, embeddings, vector search, retrieval-augmented generation, model evaluation, automation, visualization, and rapid prototyping. Embedding methods should be evaluated against the problem’s practical constraints.

Prototype and evaluate emerging tools through applied R&D while maintaining accuracy, confidentiality, and defensibility.

Participate in code review, communicate findings and trade-offs, and create reusable examples, templates, documentation, and training materials.

A hands-on, resourceful approach to ambiguous problems and a willingness to learn beyond a narrow technical specialty.

Sound judgment when handling confidential information, evaluating AI-generated output, and documenting assumptions or limitations.

Strong collaboration, organization, and communication skills, with the flexibility to manage parallel workstreams and shifting deadlines., A bachelor’s degree in Computer Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Economics with strong technical coursework, or a related field; equivalent hands-on experience may also be considered.

Practical experience building an AI-enabled application, tool, or automated workflow, with the ability to explain personal contributions, technologies, performance, and limitations.

A foundation in Python, including pandas, NumPy, scikit-learn, or comparable libraries, and working knowledge of SQL, relational concepts, joins, aggregation, and filtering.

Foundational statistics, analytics, machine learning, or experimental evaluation knowledge, plus exposure to Generative AI, prompt design, and retrieval workflows.

Familiarity with Git, notebooks, testing, documentation, code review, and reproducible development practices.

Availability to begin full-time employment in July 2027.

Preferred Qualifications

Familiarity with Azure or comparable cloud environments.

Coursework, internships, research, or independent projects involving heterogeneous data and responsibly evaluated AI-assisted development.

Thinking Minds’ client offers a collaborative learning environment, guidance from experienced technical colleagues, a competitive benefits package, and a performance-based bonus program for eligible roles.