Machine Learning Engineer

Workmode: Permanent REMOTE

Work location: PAN India

We are looking for a highly skilled and experienced Machine Learning Engineer / MLOps Engineer to join our team. The ideal candidate will have a strong background in machine learning development and deployment, with a focus on optimizing and scaling machine learning models in production environments. Experience in one or more of the following domains: manufacturing, retail/ecommerce, banking/financial services, or personalization is highly preferred.Key Responsibilities:

1. Machine Learning Model Development: Develop, train, and optimize machine learning models for various applications within the chosen domain(s), such as demand forecasting, fraud detection, recommendation systems, or customer segmentation.
2. Data Engineering: Design and implement data pipelines for ingesting, processing, and transforming large-scale datasets. Ensure data quality, consistency, and reliability for machine learning model training and inference.
3. Model Deployment and MLOps: Implement scalable and reliable infrastructure for deploying machine learning models into production environments. Automate model deployment, monitoring, and maintenance using MLOps best practices and tools.
4. Performance Optimization: Optimize machine learning models and algorithms for performance, scalability, and efficiency. Fine-tune hyperparameters, experiment with different architectures, and implement optimization techniques to improve model accuracy and speed.
5. Model Evaluation and Monitoring: Develop robust evaluation metrics and monitoring frameworks to assess the performance and health of deployed machine learning models. Implement proactive alerting and remediation strategies to address issues in real-time.

Requirements:

1. Education: Bachelor's degree or higher in Computer Science, Engineering, Statistics, Mathematics, or related field. Advanced degree (Master's or Ph.D.) preferred.
2. Experience: Minimum of 4-6 years of professional experience in machine learning development and deployment. Experience in MLOps
3. Technical Skills:
• Proficiency in programming languages such as Python, R, or Scala.
• Strong understanding of machine learning algorithms, statistical modeling, and data analysis techniques.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or Spark MLlib.
• Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Familiarity with MLOps tools and platforms for model deployment, monitoring, and automation (e.g., MLflow, Kubeflow, TensorFlow Extended).
4. Domain Knowledge: Familiarity with one or more of the following domains: manufacturing, retail/ecommerce, banking/financial services, or personalization. Understanding of domain-specific data sources, challenges, and business objectives is preferred.
5. Communication Skills: Excellent verbal and written communication skills. Ability to effectively communicate complex technical concepts to non-technical stakeholders.

If you meet the above qualifications and are passionate about leveraging machine learning to drive business impact in diverse domains, we encourage you to apply for this exciting opportunity. Join us in shaping the future of AI-driven solutions