Experience: Candidates should have at least 5-7 years of experience in the field of machine learning, with a strong track record of delivering successful machine learning projects. Experience with deep learning techniques such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) Technical Skills: Strong programming skills in languages such as Python, Java, or C++, along with experience in machine learning frameworks like Databricks ML Flow, TensorFlow, Sagemaker or PyTorch. Knowledge of big data technologies like Hadoop, Spark, or Kafka is a must. Problem-solving Skills: The ability to develop and implement innovative solutions to complex problems is crucial for this role. Communication Skills: Excellent communication skills, both written and verbal, are essential for collaborating with team members, presenting findings to stakeholders, and explaining technical concepts to non-technical audiences. Leadership Skills: As a Staff Machine Learning Engineer, the ability to lead and mentor junior members of the team is important, as is the ability to work collaboratively with other teams and stakeholders. Design, develop and launch efficient and reliable machine learning algorithms and models that help to enable insights. Test and evaluate the performance of machine learning models and systems using various metrics, such as accuracy, precision, recall, and F1 score. Analyze the results and identify areas for improvement. Act as an anchor and help build a center of excellence for ML. Mentor and coach junior machine learning engineers, data scientists, and other team members. Ensure the scalability, reliability, and performance of machine learning models. Stay up to date with the latest machine learning research and technologies. Identify opportunities to generate maximum business impact using AI/ML.