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