Principal AI Engineer

About the Company

Our client is a well-funded AI-based EdTech partnering closely with multiple government entities to deliver learning solutions impacting students at a population scale.

Roles and Responsibilities

• Develop and implement state-of-the-art NLP, Computer Vision, Speech, GenAI
• techniques.
• Design, build, fine-tune, and evaluate LLMs, VLMs, and SLMs for conversational,
• multimodal, and educational use cases.
• Conduct research and experiments in deep learning, machine learning, Generative
• AI, and foundation models to support the development of scalable AI techniques.
• Lead the instruction fine-tuning of Small Language Models (SLMs) (utilizing
• LoRA/PEFT) on proprietary datasets to achieve state-of-the-art performance.
• Architect deep temporal models (LSTMs/Transformers/DMSW) that ingest
• multimodal behavioral data to build predictive models (e.g. predict student dropout
• risks and learning gaps weeks in advance).
• Design, implement, and optimize robust Multi-Agent Systems where specialized
• agents (Tutors, Retrievers, Critics) collaborate to solve complex pedagogical tasks.
• Architect end-to-end AI pipelines capable of handling massive throughput (10M+
• daily active users) with sub-second latency constraints. Optimize the high-stakes
• trade-offs between model complexity (accuracy), inference latency, and unit
• economics.
• Mentor junior AI Engineers and work with data scientists, fostering a culture of
• technical excellence.

Skills and qualifications

• Experience: 5+ years in Software Engineering, with at least 5+ years deeply focused
• on AI/ML. A proven track record of designing and deploying AI models to production
• at scale (millions of users).
• Education: MS or PhD in Computer Science, AI or a related field with experience in
• machine learning and data analysis.
• Generative AI Stack: Deep expertise in the modern LLM ecosystem: Transformers
• (Hugging Face), Orchestration frameworks (LangChain, LangGraph, LlamaIndex),
• Vector Databases (Milvus, Pinecone, Weaviate), and Inference Optimization (vLLM,
• TGI).
• Assessment Technology: Experience with Optical Character Recognition and
• psychometric models (Item Response Theory, DKT) is a significant differentiator.
• Hands-on experience in ML model development, fine-tuning, and deployment,
• including productionizing AI/GenAI systems.
• Deep Learning Mastery: Expert-level proficiency in PyTorch or TensorFlow. Strong
• theoretical and practical understanding of sequence models (RNNs, LSTMs,
• Transformers) and their application in NLP and Time-Series forecasting.
• Strong programming skills in Python, node.js or other relevant programming
• languages.
• Familiarity with machine learning libraries, such as TensorFlow, Keras, PyTorch,
• scikit-learn, Conversational frameworks like Rasa, DialogFlow, Lex, etc.
• Data & Cloud Engineering: Experience with big-data processing and cloud-native AI
• infrastructure (AWS Bedrock, SageMaker, or GCP Vertex AI) is a huge plus.
• Strategic Competencies: A "Systems Thinking" mindset. Exceptional ability to
• communicate complex AI concepts to non-technical stakeholders (government
• officials, product leaders). A demonstrated passion for mentorship and team building.

What's On Offer

• An opportunity to create a impact at nation-level, working closely with multiple government bodies.
• This is a high-ownership, hands-on leadership role at the intersection of deep-tech architecture, public-scale delivery, and mission-critical reliability.