Software AI Engineer

We are seeking a skilled and experienced 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, cloud platforms, and production-grade model deployment. This role involves collaborating with cross-functional teams to create intelligent applications, optimize model performance, and seamlessly integrate AI/ML solutions into existing systems and business workflows.

Key Responsibilities
- Design, develop, train, and optimize machine learning and deep learning models for real-world applications.
- Build AI/ML pipelines that handle 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 as needed.
- 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 efficient 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 such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Practical experience deploying AI/ML models into production environments.
- Knowledge of containerization and orchestration tools like Docker and Kubernetes, as well as CI/CD pipelines and model-serving technologies.
- Familiarity with MLOps tools such as MLflow or Kubeflow.
- Experience developing RESTful APIs using FastAPI, Flask, or Django.
- Working knowledge of SQL, databases, Git, 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 and contribute to impactful projects within a collaborative and innovative environment. Candidates who are passionate about advancing AI/ML solutions and eager to grow their expertise in production-grade deployments will find this role rewarding.