AI/ML Engineer

Job Summary

AI/ML Engineer

machine learning algorithms

Python programming

model development

data pipelines

production deployment

Key Responsibilities

• Design and implement machine learning models and AI solutions for business use cases
• Build and optimize data preprocessing pipelines for training and inference
• Train, evaluate, and fine-tune supervised, unsupervised, and deep learning models
• Collaborate with data engineers, product teams, and software developers
• Deploy ML models into production using APIs, Docker, or cloud-native tools
• Monitor model performance and retrain/update models as needed
• Document model architectures, experiments, and performance metrics
• Research and stay updated on new AI/ML trends and tools
  

Required Skills And Experience

• Strong programming skills in Python (NumPy, Pandas, Scikit-learn, etc.)
• Experience with deep learning frameworks like TensorFlow, Keras, or PyTorch
• Solid understanding of machine learning algorithms, data structures, and statistics
• Experience with NLP, computer vision, or time series analysis is a plus
• Familiarity with tools like Jupyter, MLflow, or Weights & Biases
• Understanding of Docker, Git, and RESTful APIs
• Experience with cloud platforms such as AWS, GCP, or Azure
• Strong problem-solving and communication skills
  

Nice To Have

• Experience with MLOps tools and concepts (CI/CD for ML, model monitoring)
• Familiarity with big data tools (Spark, Hadoop)
• Knowledge of FastAPI, Flask, or Streamlit for ML API development
• Understanding of transformer models (e.g., BERT, GPT) or LLM integration
  



Education

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field
• Certifications in Machine Learning/AI (e.g., Google ML Engineer, AWS ML Specialty) are a plus