Machine Learning Engineer

About the Company

One of our clients is a fast-moving AI engineering team building next-generation multi-agent systems that automate complex business workflows. Their focus is on creating scalable, secure AI agents that integrate with enterprise software and drive measurable operational impact. This role is an opportunity to build production-grade AI systems at scale and influence the architecture of agentic workflows used in real business settings.

Role Overview

They are seeking an experienced AI Agent Engineer who specializes in large language models (LLMs), agent architectures, and tool-enabled AI systems. You will design, implement, and deploy multi-step agent pipelines, build robust ML pipelines for model training and fine-tuning, and manage inference infrastructure. This role blends ML research, systems engineering, and product-oriented delivery.

Key Responsibilities

• Design and implement complex, multi-step agent pipelines using both open- and closed-source LLMs.
• Build tools and adapters that allow agents to interact securely with enterprise applications and APIs.
• Ensure agent behavior aligns with business objectives, reliability targets, and relevant compliance requirements.
• Create data generation, processing, and labeling pipelines to support model training and fine-tuning.
• Implement training and evaluation workflows for LLMs and downstream agent components.
• Run experiments to improve agent reasoning, tool-use, and task completion metrics.
• Operate and optimize inference endpoints and related serving infrastructure on cloud platforms.
• Implement monitoring, observability, and performance testing for deployed models and agents.
• Contribute to secure, scalable CI / CD for model release and rollbacks.

Required Qualifications

Preferred Qualifications

What They Offer

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering and Research

Industries

Software Development

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