Machine Learning Engineer III

Job Summary:

We are seeking a highly motivated and experienced Machine Learning Engineer to join our dynamic AI and Data Science team. In this role, you will design, build, and deploy scalable machine learning models and solutions to solve real-world problems and enhance our products and services.

Key Responsibilities:

• Design, develop, and deploy machine learning models into production systems.
• Work closely with data scientists, software engineers, and product managers to build ML-powered features.
• Perform data preprocessing, feature engineering, and model evaluation.
• Develop APIs and services to expose ML models for internal and external use.
• Monitor, maintain, and improve deployed models in terms of performance and accuracy.
• Conduct research to stay updated with the latest ML techniques and tools.
• Optimize model training and inference pipelines for efficiency and scalability.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
• 3+ years of experience in machine learning, data science, or related roles.
• Proficient in Python and machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
• Experience with model deployment tools such as Docker, Kubernetes, or cloud services (AWS/GCP/Azure).
• Strong understanding of algorithms, statistics, and data structures.
• Familiarity with RESTful APIs and microservices architecture.
• Solid experience with version control (Git) and collaborative development workflows.

Preferred Qualifications:

• Ph.D. in a relevant field is a plus.
• Experience with MLOps tools (e.g., MLflow, TFX, Kubeflow).
• Exposure to deep learning, NLP, or computer vision projects.
• Knowledge of data pipelines and ETL frameworks like Airflow or Spark.

Benefits:

• Competitive salary and performance bonuses
• Flexible working hours and remote work options
• Health, dental, and vision insurance
• Paid time off and holidays
• Learning and development budget
• Collaborative and inclusive work culture