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.
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