AI/ML Engineer

Improbable; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Improbable is seeking an AI/ML Engineer to develop production AI systems for supply chain intelligence. You will design and implement full-stack production AI systems, focusing on FastAPI endpoints, data processing pipelines, and low-latency inference services.

You will work closely with the Principal Engineer to shape architecture for ingesting and processing global supply chain data, and mentor teammates through code reviews to raise overall ML development quality.

Qualifications

• Strong Python experience with production ML systems.
• Experience building production-grade AI systems with low latency.
• Hands-on experience with FastAPI and data processing pipelines.
• Ability to mentor team members through code reviews and collaboration.

Responsibilities

• Design and implement full-stack production AI systems for supply chain intelligence.
• Architect and optimize low-latency inference services and data pipelines.
• Collaborate with Principal Engineer to shape foundational AI architecture and mentor teammates.

Skills

Python

ML integration

FastAPI

Data pipelines

Inference services

Mentoring

Job description

Improbable seeks an AI/ML Engineer to develop production AI systems for supply chain intelligence. This role involves building robust infrastructure for domain-specific language models. Candidates with strong Python and ML integration experience should apply.

In this role, you will design and implement full-stack production AI systems, focusing on building FastAPI endpoints, data processing pipelines, and inference services. You will be responsible for the architecture, ensuring that the systems are not only functional but also production-grade with low latency.

You will work closely with the Principal Engineer to shape the foundational architecture for ingesting and processing global supply chain data. Your responsibilities will include mentoring team members through code reviews and collaborative coding, enhancing the overall quality of ML system development within the team.