Engineering & Computer Science Subject Matter Expert (Master/Phd)

Overview

Job Title : Engineering & Computer Science Subject Matter Expert – AI Training & Content Development

About Innodata :

Innodata (NASDAQ : INOD) is a global leader in data engineering and AI-powered solutions, partnering with 4 of the world’s top 5 technology companies and serving over 2,000 enterprise clients worldwide. With a workforce of 5,000+ subject matter experts and operations in 13 cities globally, Innodata is at the forefront of Machine Learning (ML), Natural Language Processing (NLP), and Large Language Model (LLM) development. We combine deep domain expertise, advanced AI / ML capabilities, and high-security infrastructure to build next-generation AI systems that are more intelligent, context-aware, and safe.

About the Role :

We are seeking highly skilled Engineering & Computer Science Subject Matter Experts (SMEs) with exceptional technical expertise, research ability, and content creation skills to join our AI / LLM training team. In this role, you will design, curate, and review technical content that enhances AI’s understanding of engineering disciplines, computing systems, algorithms, software engineering principles, and applied technologies. Your expertise will directly shape how AI systems reason about, solve, and communicate engineering and computer science concepts.

Content Development :

• Create high-quality technical content, including:
• Problem-solving exercises and step-by-step solutions.
• Theoretical and applied engineering summaries.
• Software design patterns, coding best practices, and algorithm explanations.
• Technical documentation, system architecture diagrams, and engineering principles.
• Cover multiple domains, including (but not limited to):
• Engineering: Electrical, Mechanical, Civil, Industrial, Systems, and Robotics.
• Computer Science: Data Structures, Algorithms, Operating Systems, Computer Architecture, Cybersecurity, and AI / ML.
• Software Engineering: Full-stack development, DevOps, Cloud Computing, Databases, and Distributed Systems.

Model Evaluation & AI Training :

• Review AI-generated responses to complex technical questions for accuracy and completeness.
• Identify and correct conceptual gaps, computational errors, and ambiguous phrasing.
• Develop evaluation rubrics to improve reasoning and problem-solving capabilities in AI.

Research & Technical Collaboration :

• Collaborate with engineers, computational linguists, and AI researchers to refine datasets and model performance.
• Contribute insights on systems engineering principles, optimization, and software development lifecycles.
• Support AI ethics and safety efforts to ensure responsible deployment of technical knowledge.

• Eligibility Criteria: Master’s or PhD in Engineering, Computer Science, Software Engineering, or related STEM field.
• Strong foundation in:
• Core Engineering Principles (Mechanical, Electrical, Civil, Systems, etc.).
• Computer Science Concepts (Algorithms, Data Structures, Computational Complexity, etc.).
• Software Development Practices (Agile, DevOps, CI / CD).
• Demonstrated expertise in technical writing, curriculum development, or advanced R&D projects.

• Familiarity with ML, NLP, and LLMs (a plus).
• Hands-on experience with Python, C++, Java, or similar programming languages.
• Knowledge of distributed systems, cloud computing, and cybersecurity fundamentals.
• Strong ability to simplify complex concepts for varied audiences.

• Influence AI reasoning in engineering and computing at a global scale.
• Work with world-class researchers, linguists, and technologists.
• Contribute to cutting-edge AI development shaping industries worldwide.
• Remote-first, flexible work arrangements and research-driven culture.

• Candidates must complete an English Language Assessment.
• This step is mandatory and non-billable.