Machine Learning Engineer

Key Responsibilities

• Model Development: Design, train, and optimize machine learning models for production use.
• Architecture & Scalability: Build robust, scalable ML pipelines and data processing systems.
• Research & Innovation: Stay ahead of emerging AI/ML trends and integrate cutting-edge techniques.
• Collaboration: Work closely with data scientists, software engineers, and product managers to align ML solutions with business goals.
• Mentorship: Guide and review the work of junior ML engineers and data scientists.
• Deployment & Monitoring: Implement CI/CD for ML models, ensuring performance, reliability, and fairness.

Required Skills

• Technical Expertise:
• Strong proficiency in Python, TensorFlow, PyTorch, scikit-learn.
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools.
• Deep understanding of NLP, Computer Vision, or Recommendation Systems.
• Strong grasp of data structures, algorithms, and distributed computing.
• Soft Skills: Excellent problem-solving, leadership, and communication abilities.

Preferred Experience

• Leading ML projects from concept to deployment.
• Working with big data technologies (Spark, Hadoop).
• Applying ethical AI and bias mitigation strategies.