Who we are:
Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are the AI technology solutions provider-of-choice to 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.
By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of clean and optimized digital data to all industries. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.
Our global workforce includes over 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years.
About the Role
We’re looking for curious, hands-on engineers eager to build the next wave of Generative AI applications. As an Associate Software Engineer, you’ll work with experienced AI architects and data scientists to develop, test, and evaluate GenAI-powered systems that solve real enterprise problems.
This is a great opportunity for recent grads or early-career professionals passionate about Python programming, prompt engineering, and GenAI application evaluation.
Key Responsibilities
Prototype LLM + retrieval pipelines with safety and filtering.
Operate knowledge graph/ vector DBs (Pinecone, Weaviate) and manage embeddings.
Build FastAPI services for search, recsys, and memory.
Design resilient systems with caching, retries, observability.
Run data pipelines for large-scale indexing and embeddings.
Capture personalization signals (search, chat, purchase).
Optimize for low-latency APIs & high-throughput pipelines.
Collaborate with research and product on evaluation and UX.
Build and test Python-based scripts, APIs, and microservices supporting GenAI workflows.
Assist in prompt engineering, data preparation, and evaluation of GenAI models (e.g., GPT, Claude, Gemini, Llama).
Help design and run experiments to measure model quality, reasoning, and response consistency.
Collaborate with project and solution teams to prototype new GenAI use cases.
Document findings, test cases, and improvement ideas for continuous learning.