AL ML Engineer

Job Summary:

AI/ML Engineer

Key Responsibilities:

• Design, build, and optimize

  machine learning models

  for prediction, classification, NLP, computer vision, or recommendation systems.
• Develop and maintain

  end-to-end ML pipelines

  from data preprocessing to deployment and monitoring.
• Collaborate with data scientists, data engineers, and software developers to integrate AI models into production environments.
  
• Conduct exploratory data analysis (EDA) and feature engineering to improve model accuracy and performance.
  
• Implement

  MLOps best practices

  , including version control, CI/CD, model serving, and performance monitoring.
• Evaluate model performance using appropriate metrics and tune hyperparameters for optimal results.
  
• Research and prototype new algorithms and frameworks to improve model efficiency and scalability.
  
• Document technical processes, model architectures, and deployment workflows.
  
• Stay updated with the latest advancements in AI, ML, deep learning, and related technologies.
  

Required Skills and Qualifications:

• Bachelor’s or Master’s degree in

  Computer Science, Data Science, Artificial Intelligence, or a related field

  .
• 3–6+ years of experience in

  machine learning engineering, data science, or applied AI development

  .
• Proficiency in

  Python

  and ML/DL frameworks such as

  TensorFlow, PyTorch, Scikit-learn, XGBoost, Keras

  .
• Strong understanding of

  data structures, algorithms, and statistical modeling

  .
• Hands-on experience with

  cloud platforms (AWS, Azure, GCP)

  for model training and deployment.
• Experience with

  containerization and orchestration tools

  (Docker, Kubernetes).
• Knowledge of

  SQL, NoSQL databases

  , and data pipeline tools (Airflow, Spark, etc.).
• Familiarity with

  MLOps tools

  like MLflow, Kubeflow, or SageMaker.
• Excellent problem-solving, debugging, and optimization skills.
  

Preferred Qualifications:

• Experience with

  Natural Language Processing (NLP)

  or

  Computer Vision (CV)

  projects.
• Understanding of

  Generative AI, LLMs (e.g., GPT, LLaMA, Claude)

  and fine-tuning techniques.
• Knowledge of

  reinforcement learning

  ,

  graph neural networks

  , or

  time-series forecasting

  .
• Contributions to open-source ML/AI projects.
  
• Certifications in AI/ML or cloud technologies (e.g., AWS Certified Machine Learning).
  

Soft Skills:

• Strong analytical and critical-thinking abilities.
  
• Excellent communication skills for translating complex concepts into business insights.
  
• Collaborative mindset with the ability to work in cross-functional teams.
  
• Self-motivated, curious, and eager to learn emerging AI technologies.