Machine Learning Engineer

About The Opportunity

• Translate business requirements into scalable ML models and end-to-end pipelines.
• Develop, train, and validate supervised and unsupervised models using Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Design and implement data preprocessing and feature engineering workflows to ensure high data quality.
• Deploy models as RESTful services using Docker, Kubernetes, and cloud-native technologies (AWS/GCP/Azure).
• Monitor model performance in production, implement A/B testing, retraining pipelines, and performance tuning.
• Collaborate cross-functionally with Data Engineers, DevOps, and Product teams to integrate ML components into applications.
  

Skills & Qualifications

• Bachelor’s or Master’s in Computer Science, Engineering, or related field.
• Proficient in Python and core ML libraries: TensorFlow, PyTorch, scikit-learn.
• Hands-on experience designing, training, and evaluating ML models (classification, regression, clustering).
• Strong expertise in data preprocessing, feature engineering, and pipeline development.
• Experience deploying models using Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP).
• Solid understanding of software engineering best practices: Git, CI/CD, and unit testing.
  

Preferred

• Experience with MLOps frameworks: Kubeflow, MLflow, or SageMaker.
• Familiarity with NLP, computer vision, or time-series forecasting.
• Knowledge of big data technologies: Spark, Hadoop, or Airflow.
• Experience automating monitoring and retraining pipelines.
• Exposure to API design and microservices architecture.
• Certifications in cloud ML services (AWS Certified ML Specialty, Azure AI Engineer).
  

• Competitive salary, comprehensive health insurance, and performance-based bonuses.
• Collaborative on-site environment with continuous learning, mentorship, and knowledge-sharing.
• Access to cutting-edge AI tools, industry conferences, and certification support.