AI / ML Engineer

Kimber; United States; Remote; USD 77,000 - 133,000; Full time

Job summary

Kimber is seeking an AI/ML engineer to build and productionize pipelines powering real customer products, including LLM features, retrieval, and predictive systems. The role spans data engineering, system design, deployment, monitoring, and ongoing maintenance of models in real-world conditions.

The position blends hands-on model work with advisory duties for clients, collaborating with full-stack and platform teams to integrate models into applications.

Qualifications

• 3+ years building and shipping ML/AI systems.
• Strong Python skills with ML/data tooling.
• Hands-on with LLM APIs, embeddings and vector search.
• Understanding model evaluation, data quality and production monitoring.

Responsibilities

• Design and build ML/LLM pipelines from data preparation to deployment.
• Develop retrieval-augmented generation, agent, and workflow automation systems.
• Define evaluation approaches and monitor model quality, cost, and latency.
• Partner with engineers to integrate models into client applications.
• Advise clients on value of AI vs simpler approaches.

Skills

ML pipeline design

Python programming

LLM APIs

Embeddings & vector search

Production monitoring

Stakeholder communication

Tools

ML tooling

Cloud services

Data pipelines

Job description

Role overview

An AI and ML engineering position building and productionizing pipelines that power real customer products, including LLM features, retrieval, and predictive systems. The work spans data engineering, system design, deployment, monitoring, and the ongoing maintenance of models that must perform reliably under real-world conditions. It blends hands-on model and pipeline work with client-facing advisory responsibilities.

Responsibilities

• Design and build machine learning and LLM-powered pipelines from data preparation through deployment.
• Develop retrieval-augmented generation, agent, and workflow automation systems.
• Define evaluation approaches and monitor model quality, cost, and latency in production.
• Partner with full-stack and platform engineers to integrate models into client applications.
• Advise clients on where AI creates real value and where simpler approaches are preferable.

Requirements

• 3+ years of experience building and shipping machine learning or AI systems.
• Strong Python skills with experience using common ML and data tooling.
• Hands-on experience with LLM APIs, embeddings, and vector search.
• Understanding of model evaluation, data quality, and production monitoring practices.
• Ability to explain technical trade-offs cleary to non-specialist stakeholders.

Nice to have

• Experience with MLOps tooling and model serving on a major cloud provider.
• Experience fine-tuning models or working with synthetic data strategies.
• Awareness of GDPR and responsible AI practices.

Benefits and work setup

• Full-time position based in Dublin or remote.