Artificial Intelligence Engineer

This role is for one of the Weekday's clients

Artificial Intelligence Engineer

machine learning (ML)

deep learning

large language models (LLMs)

Requirements

Key Responsibilities

• AI Model Development: Design, train, and optimize AI and machine learning models, including supervised, unsupervised, and reinforcement learning techniques, to address complex business challenges.
• Large Language Models: Work extensively with LLMs (e.g., GPT, LLaMA, Claude, or Gemini) — fine-tuning, prompt engineering, and developing applications leveraging transformer-based architectures.
• Data Engineering & Preparation: Collect, preprocess, and analyze structured and unstructured data to ensure data quality and model performance.
• Algorithm Optimization: Research and implement advanced algorithms for tasks such as natural language processing (NLP), computer vision, and generative AI, ensuring scalability and efficiency.
• Model Deployment & Integration: Deploy AI models into production environments using MLOps best practices and ensure seamless integration with existing systems or APIs.
• Collaboration & Innovation: Work closely with data scientists, software engineers, and product teams to translate business requirements into intelligent and automated solutions.
• Research & Experimentation: Stay updated on the latest AI advancements, frameworks, and LLM capabilities, experimenting with new architectures and techniques to drive continuous improvement.
• Performance Monitoring: Develop evaluation metrics and continuously monitor model accuracy, fairness, and bias to maintain ethical and reliable outcomes.
  

Required Skills & Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field.
• Experience: 3-5 years of professional experience in AI and ML model development, with proven contributions to real-world deployments.
• Technical Proficiency:
• Strong programming skills in Python and familiarity with TensorFlow, PyTorch, Keras, or similar frameworks.
• Deep understanding of transformer architectures, embedding models, and language model fine-tuning.
• Hands-on experience with data processing tools (Pandas, NumPy, scikit-learn) and MLOps pipelines (MLflow, Docker, Kubernetes).
• Proficiency in natural language processing, predictive analytics, and model evaluation metrics.
• Exposure to cloud AI platforms (AWS SageMaker, Azure ML, or Google Vertex AI).
  

Preferred Attributes

• Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG) pipelines.
• Ability to design prompt engineering strategies and fine-tune LLMs for custom use cases.
• Strong analytical, problem-solving, and mathematical reasoning skills.
• Excellent communication and collaboration skills, with a passion for innovation and learning