AI Engineer

particle41llc; United States; Remote; USD 110,000 - 170,000; Full time

Job summary

particle41llc is looking for a hands-on ML Engineer to develop and deploy machine learning and generative AI solutions that meet business needs, from data prep to deployment and ongoing monitoring.

You will build and evaluate models, create retrieval-augmented and conversational AI systems, and collaborate with data engineering to integrate models into APIs and microservices in production environments.

Qualifications

• Bachelor's or master's degree in CS, engineering, data science, or related field.
• 3+ years hands-on experience developing and deploying AI/ML systems.
• Strong Python skills with frameworks such as PyTorch, TensorFlow, scikit-learn, or modern language model tooling.
• Understanding of ML fundamentals, statistics, algorithms, and data structures.
• Experience deploying production models via APIs or microservices and monitoring them.

Responsibilities

• Build, train, evaluate, deploy, and monitor machine learning models across the development lifecycle.
• Create generative AI systems, including retrieval-augmented applications, agent workflows, and conversational agents.
• Partner with data engineering on pipelines, feature stores, and orchestration; integrate models into APIs and cloud deployments.
• Improve solutions for reliability, scalability, performance, and cost, and monitor for drift, bias, fairness, and other production issues.
• Document experiments, data provenance, and design decisions, and communicate with clients to translate business needs into AI solutions.

Skills

Python

ML deployment

PyTorch

TensorFlow

APIs/microservices

Education

Bachelor's/Master's in CS/Engineering/Data Science

Tools

PyTorch

TensorFlow

scikit-learn

APIs/microservices

Job description

Role overview

Develop and operate machine learning and generative AI solutions that address business needs, from data preparation through deployment and ongoing monitoring. The role combines hands‑on model engineering with production integration and direct collaboration with technical teams and client stakeholders.

Responsibilities

• Build, train, evaluate, deploy, and monitor machine learning models across the development lifecycle.
• Create generative AI systems, including retrieval‑augmented applications, agent workflows, and conversational agents.
• Partner with data engineering teams on pipelines, feature stores, and orchestration; integrate models into APIs, microservices, and cloud deployments.
• Improve solutions for reliability, scalability, performance, and cost, and monitor for drift, bias, fairness, and other production issues.
• Document experiments, data provenance, and design decisions, and communicate with clients to turn business needs into practical AI solutions.

Requirements

• A bachelor’s or master’s degree in computer science, engineering, data science, or a related field.
• At least three years of hands‑on experience developing and deploying AI or machine learning systems.
• Strong Python skills and experience with frameworks such as PyTorch, TensorFlow, scikit‑learn, or modern language model tooling.
• Understanding of machine learning fundamentals, statistics, algorithms, and data structures.
• Experience deploying production models through APIs or microservices and supporting their monitoring.
• Ability to adapt to changing priorities and explain technical results clearly.

Nice to have

• Experience with vector databases, retrieval‑augmented generation, agent workflows, or building and fine‑tuning large language models.
• Familiarity with speech technologies, computer vision, time‑series analysis, multimodal AI, or MLOps platforms.
• Contributions to research publications, open‑source projects, or personal AI/ML projects.