AI Engineer

What If Job Seekers Didn’t Have to Search 10 Job Boards?

CyOpsPath is bringing jobs from 10 job boards into one place, focusing on time-sensitive opportunities that job seekers can act on now.

We are seeking a skilled and innovative AI Engineer to design, develop, and deploy intelligent systems and scalable machine learning solutions for our clients.

Key Responsibilities

• Model Development & Deployment: Design, build, train, and deploy scalable artificial intelligence and machine learning models to solve complex operational challenges.
• Architecture & Infrastructure: Architect scalable data pipelines and backend infrastructure using distributed frameworks like Apache Spark to process large-scale datasets.
• NLP & Deep Learning Integration: Apply advanced Natural Language Processing (NLP) techniques and deep learning neural network architectures to unstructured data workflows.
• Performance Optimization: Monitor, evaluate, and fine-tune existing production models for speed, accuracy, scalable inference, and minimal latency.
• Cross-Functional Collaboration: Partner with data science, software engineering, and product management teams to define requirements, integrate AI features, and drive product innovation.
• Code Quality & Best Practices: Maintain high code quality through rigorous code reviews, automated testing, and adherence to software engineering standards in Python, C++, and Java.

Key Requirements

Required Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field.
• Programming Skills: Strong proficiency in Python and solid engineering experience in C++ or Java .
• AI/ML Core: In-depth knowledge of machine learning fundamentals, Deep Learning frameworks (e.g., PyTorch, TensorFlow), and statistical modeling.
• Specialized Knowledge: Demonstrated experience with Natural Language Processing (NLP) , text processing, and Large Language Model (LLM) fine-tuning or implementation.
• Big Data Frameworks: Experience handling large datasets using distributed processing tools such as Apache Spark .
• Software Engineering: Solid understanding of software design principles, version control (Git), and RESTful API development.

Preferred Qualifications

• Experience deploying ML models to production environments using Docker, Kubernetes, or cloud platforms (AWS, GCP, or Azure).
• Familiarity with MLOps practices, automated CI/CD pipelines, and model monitoring tools.
• Published research or contributions to open-source AI/ML projects.

Core Competencies & Skills

• Artificial Intelligence (AI) & Deep Learning
• Natural Language Processing (NLP)
• Python, C++, Java
• Data Science & Big Data (Apache Spark)
• Computer Science Fundamentals & Algorithm Design