Artificial Intelligence (AI) Engineer

Job Overview

We are seeking an innovative and results-driven Artificial Intelligence Engineer to join our technology team. In this role, you will design, build, test, and deploy production-ready AI models, machine learning systems, and machine learning pipelines. You will collaborate closely with software engineers, product managers, and data engineers to integrate cutting-edge machine learning and generative AI capabilities into our core applications and products.
Key Responsibilities

• Design, build, and maintain robust machine learning (ML), deep learning, and natural language processing (NLP) models to solve complex business problems.
• Architect end-to-end AI/ML pipelines, including data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Fine-tune, evaluate, and integrate Large Language Models (LLMs) and generative AI techniques into existing product ecosystems.
• Deploy models to production environments using API endpoints, containerization tools, and cloud infrastructure.
• Monitor operational model performance, optimize inference speed and latency, and retrain models to address data drift.
• Implement best practices for software engineering, version control, continuous integration/continuous delivery (CI/CD) for ML (MLOps), and data privacy/security.
• Collaborate with cross-functional teams to translate technical AI requirements into business deliverables.

Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
• Proven experience in software engineering and developing production-grade machine learning models.
• Strong proficiency in programming languages such as Python, C++, or Java, along with experience using framework libraries (e.g., PyTorch, TensorFlow, Scikit-learn).
• Hands-on experience with vector databases, LLM orchestration frameworks (e.g., LangChain, LlamaIndex), and model API integration (e.g., OpenAI API).
• Experience with cloud platforms (AWS, GCP, or Azure) and container technologies (Docker, Kubernetes).
• Strong understanding of MLOps, software design principles, and scalable system design.
• Excellent problem-solving, analytical, and communication skills.

Benefits

• Competitive salary and performance-based bonus structures.
• Comprehensive health, dental, and vision insurance coverage.
• Flexible work environment (hybrid or remote options available).
• Paid time off (PTO), holiday pay, and parental leave benefits.
• Continuous learning stipend for industry certifications, conferences, and courses.