Here’s what the opportunity looks like:

Location: Hybrid
Employment Type: Contract or Full-Time Opportunity via Accel DNA
Salary: $145K–$175K
Company: Accel DNA – Data & AI Talent Partners

Our client, a leader in smart manufacturing solutions, is scaling its machine learning capabilities and needs an ML Platform Engineer who can take AI models from proof-of-concept to production on the plant floor.

This is your chance to build robust ML infrastructure that drives predictive maintenance, anomaly detection, and process optimization at scale. You’ll collaborate with data scientists and production engineers to enable seamless model deployment and lifecycle management across factories.

Your Mission:

• Develop CI/CD pipelines for end-to-end ML deployment.
• Automate model monitoring, drift detection, and retraining workflows.
• Manage cloud-based and on-prem environments using Kubernetes, Docker, and Airflow.
• Build scalable infrastructure for streaming and batch inference.

What You Bring:

• Experience deploying ML models in production environments at scale.
• Proficiency with MLOps tools (MLflow, Kubeflow, Airflow) and infrastructure-as-code.
• Strong Python, containerization (Docker), and orchestration (Kubernetes) skills.
• Bonus: Experience with manufacturing, industrial IoT, or SCADA/PLC data pipelines.

🔍 Interested?

Let’s connect. Submit your profile or message us directly here on LinkedIn

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