Senior AI​/Machine Learning Engineer; Adaptive Intelligence Systems

Position: Senior AI / Machine Learning Engineer (Adaptive Intelligence Systems)
Role Overview

We are hiring a Senior AI / Machine Learning Engineer to build and scale core adaptive

intelligence systems for a next-generation learning product. This role involves designing

systems that personalize experiences dynamically based on user behavior, performance, and

interaction patterns.

This is a hands-on engineering role focused on building production-grade AI systems that

operate in real time.

Responsibilities

 Build, train, evaluate, and deploy machine learning models in production

environments.

 Design and implement data pipelines for model training and inference.

 Work with large-scale structured and unstructured datasets.

 Integrate LLMs into backend systems for reasoning, generation, or decision support.

 Implement retrieval-based systems using embeddings and vector databases.

 Optimize models and inference for latency, throughput, and cost.

 Monitor model performance and handle versioning, retraining, and rollback.

 Collaborate with backend engineers to expose models via APIs.

Required Technical Experience

Mandatory

 3+ years of hands-on experience in applied machine learning

 Strong proficiency in Python

 Experience with PyTorch or Tensor Flow

 Experience deploying models using REST / gRPC APIs

 Practical experience with LLMs (fine-tuning, RAG, prompt systems)

 Experience with vector databases and embedding workflows

 Solid understanding of model evaluation and metrics

Preferred

 Experience with real-time or low-latency inference

 Experience with MLOps tools (model registries, monitoring, CI/CD)

 Familiarity with cloud-based ML infrastructure

 Experience handling noisy or behavioral data

This Role Is a Fit If You

 Have shipped ML systems used by real users

 Are comfortable owning models end-to-end

 Prefer engineering problems over research papers

What We Value

 System-level thinking

 Clear reasoning about trade-offs

 Ownership from design to deployment