Software AI Engineer

We are seeking a talented Software AI Engineer to design, develop, deploy, and maintain scalable Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong expertise in Python programming, machine learning algorithms, deep learning frameworks, and cloud platforms. This role involves working closely with cross-functional teams to build intelligent applications, optimize model performance, and seamlessly integrate AI/ML solutions into existing business systems and workflows.

Key Responsibilities:
- Design, develop, train, and optimize machine learning and deep learning models for real-world applications.
- Build AI/ML pipelines covering data preprocessing, feature engineering, model training, evaluation, and inference.
- Develop AI-powered applications using Python and relevant AI/ML libraries and frameworks.
- Implement Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), and Retrieval-Augmented Generation (RAG) solutions where applicable.
- Deploy, monitor, and maintain production-ready AI/ML models on cloud platforms.
- Develop scalable APIs and backend services using FastAPI, Flask, or Django.
- Apply MLOps practices for model versioning, monitoring, testing, and deployment automation.
- Optimize model performance, scalability, reliability, and cloud resource utilization.
- Collaborate with cross-functional teams and provide technical guidance to junior engineers.

Required Qualifications:
- Minimum of 2+ years of professional experience in AI/ML engineering, machine learning, or a related field.
- Strong proficiency in Python and libraries such as NumPy, Pandas, SciPy, and Scikit-learn.
- Hands-on experience with AI/ML and deep learning frameworks including PyTorch, TensorFlow, or Keras.
- Solid understanding of machine learning algorithms, deep learning techniques, feature engineering, model evaluation, and hyperparameter tuning.
- Experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Practical experience deploying AI/ML models into production environments.
- Knowledge of containerization and orchestration tools such as Docker and Kubernetes.
- Familiarity with CI/CD pipelines and model-serving technologies.
- Experience with MLOps tools like MLflow or Kubeflow.
- Proficiency in developing REST APIs using FastAPI, Flask, or Django.
- Working knowledge of SQL, databases, Git version control, automated testing, and monitoring tools.

Preferred Qualifications and Benefits:
- Familiarity with Hugging Face Transformers, LangChain, LlamaIndex, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) is highly desirable.

This position offers the opportunity to work on cutting-edge AI technologies within a collaborative environment, contributing to impactful projects that drive innovation and business value.