Senior ML Engineer: Production MLOps Leader (Hybrid)

Xenon7; Cincinnati (OH); Hybrid; USD 150,000 - 185,000; Full time

Job summary

Xenon7 is seeking a Senior Machine Learning Engineer to own production ML systems, MLOps pipelines, and model integration for a life sciences client. You will drive architecture, deployment, and scaling of ML workloads across cloud and edge environments, collaborating with engineers and scientists.

This role requires 3 days onsite weekly in Indianapolis and strong cross-domain collaboration. Ideal candidates bring 10–20+ years in software engineering, MLOps, and production ML, with domain

Qualifications

• Senior-level proficiency in software engineering, MLOps, and production ML deployment.
• Experience integrating ML into OT, API workflows, and manufacturing systems.
• US work authorization; ability to work 3 days onsite weekly in Indianapolis.
• Experience in Life Sciences or chemical/process engineering domains is a plus.

Responsibilities

• Design, deploy, and maintain robust, production-grade MLOps pipelines and infrastructure for training, deployment, versioning, and monitoring.
• Implement automated model drift detection and performance monitoring in high-reliability environments.
• Operationalize production ML models into OT, API manufacturing workflows, and process control systems.
• Build low-latency, high-throughput microservices and serving architectures for live production applications.

Skills

Python

C++

PyTorch

TensorFlow

Scikit-learn

FastAPI

TorchServe

Kubeflow

MLflow

Databricks ML

Kubernetes

Docker

CI/CD

API design

Education

STEM degree

Tools

Triton Inference Server

TorchServe

AWS

Azure

GCP

Job description

Xenon7 is seeking a Senior Machine Learning Engineer to own production ML systems, MLOps pipelines, and model integration for a life sciences client. You will drive architecture, deployment, and scaling of ML workloads across cloud and edge environments, collaborating with engineers and scientists.

This role requires 3 days onsite weekly in Indianapolis and strong cross-domain collaboration. Ideal candidates bring 10–20+ years in software engineering, MLOps, and production ML, with domain