Role & responsibilities

We are looking for an experienced AI/ML Engineer to own and advance our core AI pipeline. The ideal candidate will have robust hands-on experience in Generative AI, NLP, and production ML systems. You will be responsible for maintaining, improving, and scaling the AI infrastructure that powers our child developmental assessment platform.

Key Responsibilities

- Design and build end-to-end AI pipelines for multimodal data processing including video, audio, image, and text
- Need to have worked on recommendation models, neural networks and LLMs.
- Integrate and work with Large Language Models and Vision Language Models for intelligent data extraction and reasoning
- Build and maintain RAG pipelines for grounded, context-aware AI outputs
- Develop and orchestrate agentic AI workflows for complex multi-step automation
- Build recommendation systems and personalization engines based on user behaviour and segmentation
- Deploy and maintain AI models in production cloud environments with proper monitoring and evaluation
- Expose AI capabilities as scalable REST APIs for product integration
- Perform exploratory data analysis and derive insights to support product decisions
- Collaborate with cross-functional teams to translate requirements into AI solutions
- Build evaluation and testing frameworks to ensure model quality, reliability, and safety
- Stay current with the latest advancements in LLMs, multimodal AI, and agentic systems

Required Skills and Experience

Generative AI and LLMs

- Hands-on experience building RAG pipelines including document processing, chunking strategies, embedding models, and vector databases




- Experience working with Vision Language Models for multimodal input understanding
- Strong prompt engineering skills system design, few-shot learning, chain-of-thought, structured output
- Experience with LangChain and LangGraph or similar orchestration frameworks for agentic workflows
- Familiarity with LLM API integration and multi-model pipeline design
- Understanding of hallucination mitigation and output grounding strategies in production systems

Machine Learning and Deep Learning

- Strong foundation in NLP — text classification, sequence modeling, and transformer-based architectures
- Experience fine-tuning or working with pretrained language models
- Hands-on experience with graph-based learning or relational modeling approaches
- Experience with multi-label and multi-class classification problems
- Proficiency in PyTorch and/or TensorFlow and Keras
- Experience with MongoDB for data storage, retrieval, and integration with AI pipelines

MLOps and Deployment

- Docker — containerization of ML models and services
- GCP Cloud Run or equivalent serverless deployment platforms
- CI/CD pipeline setup and management using GitHub Actions or similar tools
- FastAPI or similar frameworks for building and exposing ML model APIs
- Model versioning, monitoring, and production maintenance

What We're Looking For

- 6+ years of hands-on experience in AI/ML engineering

- Strong problem-solving mindset with ability to work on ambiguous, open-ended problems
- Experience taking AI systems from research or prototype to production
- Self-driven, ownership mindset
- Strong communication skills

📌 AI/ML ENG IMM Joinner (Bengaluru)
🏢 Spekond
📍 Bengaluru