- Design, develop, and deploy machine learning models to solve complex business problems and predict user behaviour.
- Optimise and scale real-time ML models for production environments, ensuring high availability and low latency.
- Architect and implement scalable and efficient ML pipelines and infrastructure.
- Collaborate with data scientists, engineers, and product teams to integrate ML models into production systems.
- Design and execute experimentation frameworks (A/B testing, multi-armed bandits, etc.) to evaluate model performance and improve decision-making.
- Continuously monitor and improve model performance in production, addressing concept drift, latency, and reliability challenges.
- Research and implement best practices in MLOps, automation, and deployment.
- Develop and deploy Generative AI applications, integrating LLMs and other GenAI models into production workflows.

What You Will Need
- 4 years of hands-on experience in Machine Learning and MLOps.




- Proven experience in deploying and maintaining real-time machine learning models in high-traffic consumer applications.
- Strong understanding of system design, distributed systems, and cloud-based ML infrastructure.
- Proficiency in Python, TensorFlow/PyTorch, and ML frameworks.
- Experience with experimentation design, A/B testing, and statistical evaluation of ML models.
- Knowledge of feature stores, model monitoring, and automated retraining workflows.
- Familiarity with ML lifecycle management tools (MLflow, Kubeflow, TFX, etc.).
- Strong problem-solving skills and ability to work in a fast-paced setting.

Bonus
- Experience with Generative AI models, including fine-tuning LLMs and integrating them into products.
- Exposure to reinforcement learning, bandit algorithms, or other advanced ML methodologies.

📌 Senior Machine Learning Engineer (Bengaluru)
🏢 Tokopedia
📍 Bengaluru