AI/ML Engineer

AI/ML Engineer

Experience:

Location:

Contract Duration:

Work Time:

Overview

seasoned Machine Learning and Artificial Intelligence professional

data modeling, algorithm optimization, and production-grade implementation

Key Responsibilities

• Design, develop, and deploy

  scalable machine learning and AI models

  to solve complex data-driven problems.
• Collaborate with

  cross-functional teams

  (data engineers, product managers, software developers) to integrate ML solutions into production systems.
• Evaluate model performance and continuously enhance algorithms for

  accuracy, efficiency, and scalability

  .
• Lead

  end-to-end ML lifecycle

  — data acquisition, preprocessing, feature engineering, training, validation, and deployment.
• Research, experiment, and implement

  state-of-the-art ML/AI frameworks and methodologies

  .
• Drive

  automation and optimization

  using AI techniques such as NLP, deep learning, and generative models.
• Mentor junior team members and promote

  AI/ML best practices

  across the organization.

Required Qualifications

• Bachelor’s or Master’s degree in

  Computer Science, Data Science, Artificial Intelligence

  , or a related field.
• 8–10+ years of

  hands-on experience in ML/AI model development and deployment

  .
• Strong mathematical foundation in

  statistics, probability, and linear algebra

  .
• Experience with

  model lifecycle management, data pipelines, MLOps, and monitoring

  .
• Proven ability to translate

  business challenges into AI-driven solutions

  .
• Excellent communication and stakeholder management skills.

Technical Skills

• Programming:

  Python, SQL

• ML Frameworks:

  TensorFlow, PyTorch, Scikit-learn, Keras

• Libraries:

  Pandas, NumPy

• AI Techniques:

  NLP, Computer Vision, Deep Learning, Reinforcement Learning, Generative AI, LLMs

• MLOps Tools:

  AWS SageMaker, Azure ML, Google Vertex AI, MLflow, Databricks

• DevOps Tools:

  Docker, Kubernetes, Git, CI/CD, REST APIs