Junior/Middle Machine Learning Engineer (LLM-focused) in Varex.ai

Machine Learning Engineer (LLM-Focused)

About Varex
Varex is pioneering the future of enterprise communication with our state-of-the-art Generative AI Conversational Platform. By combining advanced LLM technologies with scalable engineering, we empower businesses to deliver smarter, faster, and more personalized customer interactions.
We’re expanding our ML team and looking for a Machine Learning Engineer to help shape the next generation of AI-driven communication.

Responsibilities

LLM Fine-Tuning & Customization

• Develop and maintain fine-tuning workflows for large language models.

Prompt Engineering & Optimization

• Design, benchmark, and iterate on system and agent prompts.

Algorithm Research & Prototyping

• Explore, research, and prototype new algorithms, architectures, and model-driven features.

Backend Engineering

• Write clean, production-ready backend code.

Requirements

Basic Skills

• Strong problem-solving abilities and analytical thinking.

• Ability to clearly articulate complex ideas.

• Desire and ability to learn fast

Core Competencies

• 0.5–4 years of ML-focused backend engineering or project experience with LLMs / ML systems.

• Proficiency in Python, asynchronous programming, multithreading, and software design best practices.

• Understanding of transformer architectures, fine-tuning methods, and evaluation metrics.

• Experience with prompt engineering and prompt optimization.

• Basic understanding and some experience building and deploying RESTful  services (FastAPI, Flask, etc.).

• Comfortable with databases (SQL/NoSQL).

• Proficiency with Git.

• Solid understanding of fundamentals essential for machine learning.

Nice to Have

• Familiarity with RAG architectures, vector search engines, LangChain, or LlamaIndex.

• Experience with AWS / GCP / Azure.

• Experience with Docker and containerized environments.

What’s in it for You?

• Deep LLM Engagement: Work across the entire LLM lifecycle — research, fine-tuning, evaluation, deployment, and monitoring.

• Innovative Environment: Join a fast-moving startup culture that rewards creativity, experimentation, and leadership in generative AI.

• Real Impact: Shape the core AI systems that power next-gen enterprise communication.