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 TensorFlow

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