What you'll do:

• Collaborate with cross-functional teams to identify opportunities for AI and Data to solve business challenges
• Design and implement data pipelines to collect, process, and integrate data from various sources
• Develop and optimize machine learning and deep learning models for predictive analytics, computer vision, natural language processing, and more
• Leverage big data technologies like Hadoop, Spark, and NoSQL databases to handle large-scale datasets
• Explore and apply generative AI techniques to generate synthetic data, create content, and automate tasks
• Implement MLOps practices to streamline the model development lifecycle and enable continuous deployment
• Present findings and recommendations to stakeholders in a clear and compelling manner
• Lead cross-functional teams to deliver AI projects on time and within budget
• Stay current with the latest advancements in AI, data engineering, and related technologies

What makes you a great fit:

• 6+ years of experience in data science, machine learning, and AI
• Proficiency in Python, SQL and data visualization tools like Tableau or PowerBI
• Hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or Keras
• Knowledge of deep learning architectures and techniques for computer vision, NLP, and generative AI
• Hands-on experience with big data technologies such as Hadoop, Spark, and NoSQL databases
• Understanding of MLOps principles and tools for model versioning, monitoring, and deployment
• Familiarity with Kubernetes core concepts like pods, deployments, services, and ingress
• Strong communication and leadership skills to effectively collaborate with cross-functional teams
• Ability to work in a fast-paced, agile environment and adapt to changing priorities