Engineering & Computer Science Subject Matter Expert

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 .
Key Responsibilities:
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 .
Preferred Skills:
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.
Why Join Innodata?
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 .
Additional Information:
Candidates must complete an
English Language Assessment .
This step is mandatory and non-billable.