Job
Description
Job Description: Responsibilities: 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 Skills: 4+ years of experience in data science, machine learning, and AI • Proficiency in Python, SQL and data visualization tools like Tableau or Power BI • 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. Role & responsibilities
