Machine Learning Engineer (LLMs & Generative AI)

At Edge

We’re on a mission to eliminate geographic borders as barriers to full-time employment and fair wages. We’re creating a global HR platform ecosystem that seamlessly connects exceptional talent worldwide with North American businesses. By making global hiring easier than local hiring, we provide businesses access to a broader talent pool and accelerate their hiring process. Spread across four continents, we’re a global team disrupting how people work together.

Responsibilities

• Develop, train, and optimize machine learning models tailored to real-world business applications.
• Work deeply with LLMs and transformer architectures to build intelligent AI systems.
• Architect and maintain vector databases and embedding systems for semantic search and retrieval.
• Build and manage robust data pipelines, ETL/ELT workflows (e.g., Spark/Glue), and integrate them into Retool pipelines.
• Handle data with proficiency in both SQL and NoSQL (particularly MongoDB) systems.
• Collaborate with cross-functional teams to align AI solutions with business and compliance requirements.
• (Preferred) Contribute to deployment, monitoring, and scale of models using MLOps practices.

Requirements

Must-Have Requirements

• Proven experience in ML model development, training, and optimization.
• Hands-on expertise with LLMs and transformer architectures.
• Solid knowledge of vector databases and embedding systems.
• Strong capability in building data pipelines and ETL/ELT processes (e.g., Spark/Glue or equivalent).
• Proficiency in SQL and NoSQL databases (especially MongoDB).
• Excellent programming skills in Python and familiarity with ML/AI libraries.

Good-To-Have (Preferred) Requirements

• Experience with MLOps practices—model deployment, monitoring, and scaling.
• Familiarity with building RAG (Retrieval-Augmented Generation) systems.
• Experience in fine-tuning LLMs using techniques like LoRA, QLoRA, or PEFT.
• Working knowledge of frameworks such as Hugging Face Transformers, LangChain, or LlamaIndex.
• Exposure to deploying ML workflows on cloud platforms (AWS, GCP, Azure).

Why Join Edge?

Edge is at a pivotal growth point, offering you the rare opportunity to shape the future of global employment. Your work will directly impact business growth, enable global opportunities, and transform how people work across borders.

We’re not just offering a job — we’re inviting you to be part of a revolution.

Ready to leave a global footprint and change lives? Edge is where your vision becomes reality.