AI​/ML Engineer II

AI/ML Engineer II

The AI/ML Engineer II is a mid-level position for individuals with professional experience in designing and implementing machine learning algorithms. In this role, you will independently develop and deploy AI/ML solutions to address complex challenges, such as autonomous systems, predictive maintenance, and computer vision. You will take ownership of specific projects, perform data analysis, and optimize models for performance and scalability.

This position requires a combination of technical expertise, problem-solving skills, and the ability to collaborate with multidisciplinary teams to meet mission-critical objectives.

Responsibilities:

• Design, implement, and optimize machine learning models for applications such as object detection, signal processing, predictive analytics, and decision-making systems.
• Develop and maintain data pipelines for collecting, preprocessing, and managing large-scale datasets. Identify data gaps and propose solutions to improve data quality.
• Conduct performance testing and validation of AI/ML models using rigorous evaluation metrics. Optimize models for accuracy, efficiency, and scalability.
• Write and deploy efficient, modular code to integrate AI/ML models into operational systems, ensuring reliability and compatibility with existing platforms.
• Test AI/ML solutions in simulated environments to evaluate performance under real-world conditions. Contribute to system-level debugging and troubleshooting.
• Collaborate with hardware engineers, software developers, and systems architects to align AI/ML solutions with mission-critical requirements.
• Document technical designs, workflows, and testing procedures for internal and external use. Share findings and best practices with team members.
• Explore and integrate emerging AI/ML frameworks, tools, and methodologies to enhance system capabilities and address new challenges.
• Train, evaluate, and optimize standard AI models (ANNs, CNNs, RNNs) for supervised and unsupervised tasks.
• Implement and test basic reinforcement learning algorithms and generative models under supervision.
• Develop and integrate signal processing and computer vision modules to enhance perception and decision-making capabilities.
• Conduct simulations and performance profiling of AI/ML models on CPU/GPU architectures, identifying bottlenecks.
• Execute validation and verification procedures, analyze test results, and support system compliance with safety and reliability standards.

Qualifications You Must Have:

• Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
• 2+ years of experience in a related field.
• Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 6 years of related experience is required.
• Practical experience using machine learning frameworks (e.g., Tensor Flow, PyTorch) and applying core AI/ML techniques, including supervised, unsupervised, and introductory reinforcement learning methods.
• Hands-on experience implementing and evaluating ANNs, CNNs, and RNNs in small-scale or pilot projects. Assisted with deploying machine learning models in production or research environments.
• Proficiency in programming languages such as Python, C++, C# or Java.
• Strong understanding of supervised and unsupervised learning techniques.
• Experience deploying AI/ML solutions in production environments.

Essential Functions:

• Work extensively on a computer for coding, debugging, and integrating AI/ML systems.
• Travel occasionally to testing sites, customer locations, or conferences (up to 10-20%).
• Ability to work in a hybrid environment and manage multiple tasks effectively.