• Design and Development: Architect, build, and maintain scalable and robust AI models and systems. This includes everything from data collection and preprocessing to model training, evaluation, and deployment.
• Model Implementation: Implement and fine-tune machine learning algorithms, including but not limited to, deep learning, natural language processing (NLP), computer vision, and reinforcement learning techniques.
• Production Deployment: Oversee the entire lifecycle of AI models, ensuring seamless integration into production environments and continuous monitoring for performance and accuracy.
• Data Infrastructure: Collaborate with data engineers to design and build efficient data pipelines and infrastructure to support AI and machine learning workflows.
• Algorithm Optimization: Research and implement advanced algorithms and techniques to optimize the performance, scalability, and efficiency of our AI systems.
• Cross-Functional Collaboration: Work closely with data scientists, software developers, product managers, and other stakeholders to understand business requirements and translate them into technical solutions.
• Stay Current: Continuously research and evaluate the latest advancements in AI and machine learning to identify opportunities for innovation and improvement.
• Ethical AI: Champion and implement best practices for responsible and ethical AI development, ensuring fairness, transparency, and accountability in our models.

• Programming Proficiency: Expert-level knowledge of Python is essential. Familiarity with other languages such as R, Java, or C++ is a plus.
• Machine Learning Frameworks: Hands-on experience with popular machine learning libraries and frameworks like TensorFlow, PyTorch, scikit-learn, and Keras.
• Deep Learning: A strong understanding of deep learning architectures (e.g., CNNs, RNNs, Transformers) and their applications.
• Data Science & MLOps: Proficiency in data manipulation and analysis libraries (e.g., Pandas, NumPy) and experience with MLOps tools and practices for model versioning, CI/CD, and monitoring.
• Big Data Technologies: Experience working with large datasets and distributed computing frameworks such as Apache Spark and Hadoop is highly desirable.
• Cloud Computing: Familiarity with cloud platforms like AWS, Google Cloud Platform, or Microsoft Azure and their AI/ML services.
• Software Engineering Principles: Solid understanding of software development best practices, including version control (Git), testing, and code optimization.
• Problem-Solving: Strong analytical and critical thinking skills with the ability to tackle complex problems.
• Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Collaboration: A team player with a proven ability to work effectively in a collaborative environment.
• Adaptability: A continuous learner who is eager to stay at the forefront of a rapidly evolving field.

**We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, ethnic origin, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.**