Unlock AI Potential as a Senior Machine Learning Engineer

12 hours ago

Delhi, Delhi, India QuestionPro Full time

At QuestionPro, we are driven by our passion for Engineering Excellence. With over a decade and a half of evolution, we have adopted a wide range of technologies to develop high-quality software at scale. We collect millions of survey responses weekly and process this data to produce real-time insights ranging from cutting-edge visualizations to AI-powered solutions. Our infrastructure spans across 8 data centers globally.

We require robust, performant systems due to our scale. AI is omnipresent in our environment, and we haven't missed the bus. We have solved genuine problems with AI, not just on the GPT waiver but even before the hype. Our teams are small, independent, and empowered. Our open and flexible culture has helped people grow beyond their limits. You get to work on innovative projects directly with our Executive Team & Customers alongside some of the best Engineers.

Position Overview

You will play a key role in designing, developing, and deploying machine learning models and artificial intelligence solutions with a specific focus on leveraging OpenAI technologies. You will work closely with cross-functional teams, including data scientists, software engineers, and domain experts, to implement and optimize algorithms that enhance our products and services.

Key Responsibilities
  • Model Development & Deployment: Build, deploy, and maintain machine learning models using frameworks such as TensorFlow, PyTorch, and Scikit-learn. Implement statistical techniques (e.g., regression, clustering) and ensure scalable production integration.
  • MLOps & Automation: Develop and manage end-to-end MLOps pipelines, including model versioning, monitoring, and retraining using tools like MLflow, Kubeflow, and SageMaker. Ensure continuous integration and deployment of models (CI/CD) with Jenkins, Git, Terraform, and containerization (Docker, Kubernetes on AWS EKS).
  • Pipeline Management: Create and maintain robust data pipelines using Apache Airflow, orchestrating ML workflows on Databricks and Apache Spark (PySpark).
  • Optimization & HPC: Optimize GPU workloads and manage high-performance computing (HPC) environments. Conduct hyperparameter tuning and leverage distributed computing for model training.
  • Cross-functional Collaboration: Collaborate with data scientists, engineers, and product teams to align AI/ML initiatives with business goals. Translate business requirements into ML models and statistical analysis tasks.
  • Lifecycle Management: Oversee the full ML lifecycle, including model validation, deployment, monitoring, and regular updates using statistical metrics and performance evaluations.

The estimated annual salary for this position is around $150,000 - $200,000 depending on experience and location.

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