Artificial Intelligence and Machine Learning Specialist
2 days ago
We are seeking a talented and motivated AI/ML Software Developer to join our Lahore team. This is a fantastic opportunity for individuals passionate about artificial intelligence and machine learning to solve real-world problems. In this role, you will design, develop, and implement cutting-edge AI/ML solutions while collaborating with cross-functional teams to innovate, optimize, and deliver scalable AI-driven systems.
Responsibilities
Your primary responsibilities will include designing, developing, and deploying AI and machine learning models to address business challenges. You will create robust data pipelines and ensure the availability of clean, high-quality data for model training and evaluation. Additionally, you will optimize algorithms for scalability, performance, and efficiency and collaborate with software engineering teams to integrate AI solutions into applications and platforms. Staying updated with the latest advancements in AI, ML, and related technologies will also be crucial to your success in this role. Furthermore, you will perform data analysis and feature engineering to improve model accuracy and robustness, debug, monitor, and enhance the performance of AI systems post-deployment, and implement best practices for version control, testing, and documentation of AI models and tools.
Requirements
To excel in this position, you should possess a strong background in computer science and machine learning. Proficiency in Python programming language and experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Keras, or Scikit-learn are essential. A bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, along with 2+ years of practical experience in AI/ML development or related fields, are required. Additionally, you should have a proven track record of developing and deploying AI solutions in production environments and be proficient in creating robust data pipelines and ensuring the availability of clean, high-quality data for model training and evaluation.
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