Chief AI Innovation Officer

1 day ago

kottayam, India beBeeMachineLearning Full time

Job OverviewTritonium is an AI-powered SaaS platform that helps mobile product teams understand their users through user feedback analysis using state-of-the-art language models.Role SummaryWe are seeking a highly skilled Senior Machine Learning/AI Engineer to optimize AI inference pipelines, develop natural language processing capabilities and collaborate with product and engineering teams.Key ResponsibilitiesDesign and optimize AI inference pipelines for maximum quality and minimum cost at scale by leveraging cutting-edge technologies.Develop and improve natural language processing capabilities including sentiment analysis, topic extraction, and intent classification across multiple languages to drive business value.Build and maintain batch processing systems for cost-efficient AI workloads without compromising user experience to ensure seamless delivery of ML solutions.Collaborate closely with cross-functional teams to translate business requirements into effective ML solutions that deliver measurable results.Implement evaluation frameworks and monitoring systems to ensure AI output quality and detect model drift to minimize business risk.Research and prototype new AI/ML approaches to expand platform capabilities including predictive analytics and anomaly detection to stay ahead of the competition.Optimize prompt engineering and model selection strategies to balance accuracy, latency, and cost to maximize ROI.Contribute to architectural decisions around AI infrastructure and help establish ML engineering best practices to ensure long-term success.RequirementsBachelor's degree in Computer Science, Machine Learning or a related field to provide a solid foundation in software development and ML principles.4+ years of experience in ML engineering with demonstrated work on production NLP systems to showcase expertise in deploying complex models.Strong programming skills in Python and experience with popular ML frameworks and libraries to enable efficient development.Experience with large language models including prompt engineering, fine-tuning approaches, and inference optimization to tackle challenging projects.Hands-on experience with cloud-based AI/ML services and serverless architectures to ensure scalability and reliability.Understanding of NLP fundamentals: text classification, named entity recognition, sentiment analysis, and text embeddings to apply ML concepts effectively.Experience building data pipelines that feed ML systems at scale to ensure high-quality input data.Strong analytical skills and ability to work independently in a fully remote environment to meet deadlines.

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