One of our Global client is looking for AI/ML Development Engineer role for 100% Remote

US Citizenship is Must (Due to Nature of this job)

Manufacturing Domain Exp is Must

Title – AI/ML Development Engineer

Location- Remote

Terms- Direct Hire

Overview

Client is seeking an experienced AI/ML Developmental Engineer to build and deploy cutting-edge models that enhance our Design for Manufacturing (DFM) processes. In this role, you will work closely with manufacturing and design teams to understand Peak Nano’s unique capabilities and translate that knowledge into impactful digital tools. As part of our AI/ML team within the digital technology development group, you’ll collaborate with sibling teams (Software Development, IT, and Manufacturing Automation) and the broader organization to improve data usage and insights.

Key Responsibilities

• Develop, implement, and optimize AI/ML models that accelerate DFM processes
• Collaborate with cross-functional teams (manufacturing, design, and digital technology) to gather, analyze, and transform process data into actionable insights
• Integrate AI/ML solutions into existing workflows and business applications
• Identify and address technical roadblocks, proactively communicating progress and needs to stakeholders
• Provide data-science expertise to the wider organization, helping teams leverage their data more effectively

Required Qualifications

• Bachelor’s degree in computer science, Math, Physics, Engineering, or a related field
• At least 3 years of hands-on experience in AI/ML
• Proficiency with one or more mainstream ML frameworks (e.g., PyTorch, TensorFlow, Keras)
• Strong knowledge of Python, databases (e.g., Postgres), and version control (e.g., Git)

Preferred Qualifications

• Master’s degree in computer science, Math, Physics, Engineering, or a related field
• Prior experience in a manufacturing environment
• Proven success integrating and augmenting business applications with AI/ML solutions

Familiarity with Agile methodologies and software development best practices

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