We are a rapidly expanding AI startup transforming digital advertising with groundbreaking AI technology and innovative solutions. We are seeking a energetic and highly skilled Machine Learning Engineer to join our team and play a critical role in building the future of advertising.

As a Machine Learning Engineer, you will design, train, and improve cutting-edge machine learning models, including custom Transformer-based architectures, to predict consumer behavior. You will build and optimize the modeling components that power daily predictions for millions of consumers, owning model quality from experimentation through production.

Key Responsibilities

- Model Development: Design, build, and train machine learning models, including custom Transformer-based and other deep learning architectures, for large-scale consumer behavior prediction.
- Experimentation: Run rigorous offline and online experiments, including ablations and A/B tests, to validate model changes and quantify impact on prediction quality.
- Feature and Data Pipelines: Build and maintain feature engineering and training data pipelines that handle millions of customer predictions, with attention to provenance and reproducibility.
- Model Optimization: Improve model accuracy, latency, and efficiency through architecture choices, training techniques, and inference optimization.
- Productionization: Partner with platform and infrastructure teams to move models into production on GCP / AWS, including packaging, serving, and retraining workflows.
- Model Evaluation and Monitoring: Define evaluation metrics and monitoring for model performance, and diagnose regressions, drift, and data quality issues.
- Collaboration:



Work closely with cross-functional teams to align modeling work with business needs, product requirements, and infrastructure constraints.
- Documentation: Document model designs, experiments, methodologies, and findings comprehensively, and keep all documentation accurate and up to date.
- Innovation and Research: Stay current with new machine learning techniques, tools, and architectures, and apply them to improve existing models.

Qualifications

- Bachelor's, Master's, or PhD in Computer Science, Engineering, AI, or a related field.
- At least 2+ years of experience building and training machine learning models in production settings.
- Hands-on experience developing deep learning models, ideally including Transformer based or sequence architectures.
- Experience training and evaluating ML models on large-scale data using GCP / AWS services.
- Strong understanding of machine learning concepts, including supervised and unsupervised learning and deep learning.
- Strong programming skills in Python, with experience in frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, and Keras.
- Experience with feature engineering, training data pipelines, and model experimentation workflows.
- Familiarity with model deployment and serving, including Docker and containerized environments.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.

Nice to Have

- Prior experience working in a fast-paced startup environment.
- Experience with spatiotemporal, geospatial, or behavioral prediction problems.
- Familiarity with CI/CD for ML and automated retraining pipelines.

📌 Machine Learning Engineer (Gurugram)
🏢 ZeroToOne.AI
📍 Gurugram