AI Engineer

This role is for one of the Weekday's clients

AI Engineer

Requirements

Key Responsibilities

• Design, develop, and deploy scalable AI/ML models and algorithms to support various business and product requirements.
• Apply advanced machine learning, natural language processing (NLP), computer vision, or reinforcement learning techniques to address complex challenges.
• Perform data preprocessing, feature engineering, and exploratory data analysis to ensure high-quality datasets for model training.
• Optimize machine learning models for accuracy, efficiency, and performance in production environments.
• Collaborate with cross-functional teams including data scientists, software engineers, and product managers to deliver end-to-end AI solutions.
• Implement MLOps best practices for versioning, monitoring, retraining, and deploying models in production.
• Conduct research and stay updated on the latest developments in AI/ML technologies, frameworks, and industry trends.
• Build proof-of-concepts (POCs) to evaluate new approaches and demonstrate AI capabilities for business use cases.
• Document solutions, methodologies, and best practices for reusability and knowledge sharing within the team.
• Ensure ethical and responsible use of AI by incorporating fairness, transparency, and explainability into solutions.
  

Key Skills & Competencies

• Strong programming skills in Python (mandatory) and familiarity with libraries such as TensorFlow, PyTorch, scikit-learn, Keras, OpenCV, NLTK, or Hugging Face Transformers.
• Experience with machine learning algorithms, deep learning architectures (CNNs, RNNs, Transformers, GANs), and NLP techniques.
• Solid understanding of data structures, algorithms, probability, and statistics as applied to AI solutions.
• Proficiency in working with large datasets, data pipelines, and data preprocessing techniques.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and AI/ML services (e.g., SageMaker, Vertex AI).
• Knowledge of MLOps practices including model deployment, monitoring, CI/CD, and containerization using Docker and Kubernetes.
• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) approaches for advanced AI solutions.
• Experience integrating AI models into production systems, APIs, or enterprise applications.
• Strong problem-solving mindset with the ability to translate business requirements into technical AI solutions.
• Excellent communication and collaboration skills to work with diverse teams and stakeholders.
  

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 4-8 years of proven experience in designing and deploying AI/ML solutions in real-world applications.
• Track record of successfully delivering AI projects end-to-end, from data collection to production deployment