Machine Learning Engineer

Machine Learning Engineer – Model Training & Optimization

About Unlox

Unlox is an AI-driven learning and career platform, trusted by universities and recognized by NASSCOM. We’re building scalable AI systems to power personalized learning and career readiness for the next generation.

We are hiring a Machine Learning Engineer (Training & Optimization) who will focus on curating datasets, training, fine-tuning, and optimizing models to deliver high-performing AI systems.

Responsibilities

Curate and preprocess domain-specific datasets.

Train and fine-tune transformer-based models with LoRA, QLoRA, quantization, distillation.

Run experiments and track results to improve efficiency and accuracy.

Build training pipelines and evaluation systems for continuous improvement.

Collaborate with AI researchers and backend teams to integrate outputs into applications.

Requirements

Wrok Experience: 1 - 4 years

Proficiency in Python, PyTorch, and ML frameworks (Hugging Face, DeepSpeed, Accelerate).

Experience in fine-tuning transformer models.

Familiarity with tokenizer training, dataset pipelines, and evaluation benchmarks.

Knowledge of parameter-efficient tuning techniques.

Bonus

RLHF exposure or contributions to open-source AI projects.

Salary- As per market standards with performance based bonuses