Senior AI Engineer

SUMMARY:
As a Senior AI Engineer, you will work on challenging problems ranging from content recommendation systems and personalization engines to AI-powered newsroom tools and automated content workflows. You’ll collaborate with cross-functional teams including product managers, data scientists, engineers, and editorial teams to deliver AI solutions that directly impact millions of users.

POSITION INFO:
Key Responsibilities AI Productions Scaling : Design, develop, and deploy scalable AI\/ML systems and pipelines using cloud infrastructure (AWS, Google Cloud, Azure) Build and maintain production-grade machine learning models for content recommendation, personalization, and newsroom automation Implement MLOps practices including model versioning, automated testing, monitoring, and continuous deployment Optimize AI model performance, latency, and resource utilization for high-traffic production environments Personalization s Content Intelligence: Develop and enhance personalization algorithms that deliver relevant content experiences across web, mobile, and emerging platforms Build content classification, semantic analysis, and recommendation systems using NLP and deep learning techniques Implement real-time content processing pipelines for automated tagging, categorization, and content matching Create user profiling and behavioral analysis systems to improve content targeting and engagement Newsroom AI s Editorial Tools: Collaborate with editorial teams to develop AI-powered tools that accelerate content creation and curation Build automated content workflows including article summarization, fact-checking assistance, and content optimization Implement AI solutions for news aggregation, content deduplication, and trend analysis Develop tools for automated social media content generation and distribution optimization Technical Excellence s Innovation: Write clean, maintainable, and well-documented Python code following software engineering best practices Design and implement APIs and microservices for AI model serving and integration Conduct experiments with cutting-edge AI technologies including large language models (LLMs), transformer architectures, and generative AI Stay current with AI\/ML research and evaluate new technologies for potential implementation Collaborations Community Building: Work closely with product teams to translate business requirements into technical AI solutions Mentor junior engineers and contribute to knowledge sharing within the AI community Participate in code reviews, technical discussions, and architectural planning sessions Collaborate with data scientists to productionize research models and prototypes Required Skills and Experience Technical Qualifications: Honour's or Master's degree in Computer Science, Machine Learning, Data Science, or related technical field Minimum 5+ years of software engineering experience with at least 3 years focused on AI\/ML development Strong proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) Hands-on experience with cloud platforms (AWS SageMaker, Google AI Platform, Azure ML) and containerization (Docker, Kubernetes) Proven experience building and deploying production ML systems at scale AI\/ML Expertise: Deep understanding of machine learning algorithms, deep learning architectures, and neural networks Strong experience with NLP, text processing, and content recommendation systems Knowledge of MLOps practices including model monitoring, versioning, and automated retraining Experience with vector databases, embedding-based search, and similarity matching algorithms Familiarity with transformer models, large language models, and modern NLP architecture Software Engineering: Proficiency in API development (REST, GraphQL) and microservices architecture Experience with version control (Git), CI\/CD pipelines, and automated testing frameworks Strong understanding of database technologies (SQL, NoSQL) and data pipeline tools Knowledge of software engineering best practices including design patterns and code quality standards Preferred Experience: Experience in media, publishing, or content-driven industries Knowledge of content management systems and editorial workflows Understanding of web analytics, user behavior analysis, and A\/B testing methodologies Experience with real-time streaming data processing (Kafka, Kinesis, Pub\/Sub) Familiarity with monitoring and observability tools (Prometheus, Grafana, DataDog)