Engineering at QuestionPro

At QuestionPro We are extremely passionate about Engineering Excellence! We have constantly evolved as a team over the last decade and a half. In the quest to develop high-quality software at scale, we have adopted a wide range of technologies. We collect millions of survey responses weekly and process all this data to produce real-time insights ranging from cutting-edge visualizations to AI-powered insights. Our infrastructure is spread across 8 data centers across the globe.

Our scale forces us to build robust, performant systems. It's AI all around us! We haven't missed the bus either. We have solved some genuine problems with AI, not just on the GPT waiver but even before the hype! Our teams are small, independent & 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 with some of the best Engineers alongside you!

Position Overview:

As an AI/ML Engineer at QuestionPro, 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.

Tech Stack:

• Languages: Python (required), R, Java (preferred)
• ML Frameworks: TensorFlow, PyTorch, Scikit-learn, LangChain, LLAMA, XGBoost, LightGBM, Keras
• MLOps Tools: MLflow, Kubeflow, SageMaker, TFX (TensorFlow Extended)
• Statistical Tools: R, Python (pandas, NumPy, SciPy, statsmodels)
• Data Engineering: Apache Spark (PySpark), Databricks
• CI/CD & Orchestration: Jenkins, Git, Terraform, Apache Airflow, CircleCI
• Containerization: Docker, Kubernetes
• Data Management: SQL, NoSQL, Vector Databases

Operating Systems: Linux (required), Windows (optional)

Qualifications:

1. Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2. Proven experience in developing and deploying machine learning models, with a specific focus on OpenAI technologies, in real-world applications.
3. Proficiency in programming languages such as Python, and experience with OpenAI frameworks (e.g., GPT, Codex).
4. Strong understanding of statistical modeling, feature engineering, and data preprocessing techniques, with an emphasis on OpenAI methodologies.
5. Solid understanding of software engineering principles, version control, and collaborative development workflows.
6. Excellent problem-solving and critical-thinking skills with a keen attention to detail.
7. Effective communication skills and the ability to work collaboratively in a team environment.

If you are passionate about pushing the boundaries of artificial intelligence and machine learning, with specific expertise in OpenAI technologies, we encourage you to apply and join our team!