Senior Machine Learning Engineer

• 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 environment.

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.