AI​/ML Engineer II

Overview

The AI/ML Engineer II is a mid‑level position responsible for independently developing and deploying AI/ML solutions to address complex challenges such as autonomous systems, predictive maintenance, and computer vision. The role requires designing, implementing, and optimizing machine learning models while collaborating with multidisciplinary teams to meet mission‑critical objectives.

• 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.
• 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.

• Bachelor’s degree in computer science, mathematics, applied statistics, engineering, or a related STEM discipline.
• 2+ years of experience in a related field (or equivalent experience if lacking a degree).
• Practical experience using machine learning frameworks such as Tensor Flow or 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.

• Master’s degree in Artificial Intelligence, Machine Learning, or a related field.
• Experience with reinforcement learning or generative AI models (e.g., GANs, Transformers).
• Working knowledge of Agile or Dev Ops practices in software/ML project environments.
• Hands‑on experience with advanced ML techniques (e.g., clustering, dimensionality reduction) in coursework or projects.
• Basic experience with GPU programming (e.g., CUDA basics) or using GPUs for ML model training.
• Exposure to generative models or reinforcement learning frameworks.
• Experience analyzing and processing diverse datasets to extract insights.
• Familiarity with requirements gathering and basic deployment of ML systems.
• Awareness of hardware acceleration tools and edge AI concepts.

• 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.

Estimated starting salary range: $ – $.

SNC offers a comprehensive benefit package that includes medical, dental, and vision plans, a 401(k) plan with a 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.

This position requires the ability to obtain and maintain a Secret U.S. Security Clearance. U.S. citizenship is required; non‑U.S. citizens may not be eligible to obtain a security clearance.

SNC is an Equal Opportunity Employer committed to an environment free of discrimination. Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran, or other characteristics protected by law.