Tech
AI Engineer
You will:
Design, develop, and implement end-to-end AI/ML solutions to meet business requirements, using appropriate algorithms and techniques
Collaborate with data scientists and engineers to convert machine learning models into scalable, production-ready applications
Optimize AI/ML models for performance, accuracy, and efficiency
Maintain and improve existing AI/ML systems, ensuring high-quality and reliable performance
Perform data preprocessing, feature engineering, and model evaluation to improve model outcomes
Stay up-to-date with advancements in AI/ML research, tools, and frameworks, and incorporate new techniques and technologies as needed
Help establish and enforce best practices for AI/ML development within the organization
Work closely with product managers and stakeholders to understand project requirements and provide technical input
Clearly communicate AI/ML concepts and project results to both technical and non-technical audiences
You should have/be:
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field; PhD is a plus
2 years of experience working with AI/ML technologies, including algorithm development, model training, and deployment
Strong programming skills in Python, with experience in ML libraries such as TensorFlow, PyTorch, or Scikit-learn
Experience with big data technologies (e.g., Hadoop, Spark) and data storage systems (e.g., SQL, NoSQL)
Knowledge of various ML techniques (e.g., supervised and unsupervised learning, deep learning, reinforcement learning) and their practical applications
Familiarity with cloud-based AI/ML platforms, such as AWS SageMaker, Google Cloud AI, or Microsoft Azure ML
Excellent problem-solving skills and the ability to work independently or as part of a team
Strong communication and collaboration skills, with the ability to present complex ideas to diverse audiences
Preferred Qualifications:
Experience with natural language processing (NLP), computer vision, or speech recognition technologies
Familiarity with AI/ML model deployment and lifecycle management tools, such as MLflow or Kubeflow
Experience working in an Agile development environment
Background in a domain-specific area, such as healthcare, finance, or e-commerce, is a plus
