Principal AIML Engineer

As a Principal Machine Learning Engineer at the company, you will be instrumental in architecting, scaling, and delivering large-scale machine learning systems focused on Natural Language Processing (NLP), Large Language Models (LLMs), and advanced deep learning techniques. **Key Responsibilities:** - **End-to-End LLM System Architecture:** You will design and lead the development of advanced LLM-based systems, optimizing performance, resource utilization, and reliability. - **Scaling AI Solutions:** Lead the efforts to scale machine learning solutions across enterprise-wide applications, ensuring fault tolerance and minimal downtime. - **High-Impact ML Deployment:** Drive the large-scale deployment of LLMs and other ML models in cloud and hybrid environments, ensuring high scalability, security, and reliability. - **Deep Learning System Optimization:** Architect and optimize deep learning systems to enhance performance through techniques like distributed training and hyperparameter tuning. - **Business Alignment:** Align ML solutions with business strategies to maximize ROI from AI investments. - **AI Innovation Leadership:** Spearhead the exploration of new ML models and techniques, driving the next generation of AI applications. - **Cross-Functional Leadership & Collaboration:** Mentor AI engineers and collaborate with product teams, data engineering, and operations for seamless AI solutions. - **System Reliability and Optimization:** Ensure high system availability by implementing monitoring, logging, and alerting strategies. - **ML Governance and Compliance:** Oversee governance of AI systems to ensure ethical deployment and compliance with data privacy regulations. **Technical Expertise:** - **Advanced NLP & LLMs:** Deep expertise in building, fine-tuning, and deploying large language models such as LLaMA and Mistral families. - **Distributed Systems & Parallelization:** Expert knowledge of distributed systems and parallelized model training for large-scale deployments. - **Deep Learning Frameworks:** Advanced experience with PyTorch, TensorFlow, and proficiency in software engineering and system design skills. - **Cloud and Infrastructure Expertise:** Experience in architecting fault-tolerant, distributed ML systems across multi-cloud platforms. **Must-Have Skills:** - Excellent communication skills - Strong team player - In-depth understanding of scalable and reliable solutions - Willingness to work from the office **Nice to Haves:** - Experience in deploying multimodal AI solutions - Proven track record of managing large-scale ML systems in production **Qualifications:** - 8+ years of experience with a Bachelor's degree, 6+ years with a Master's, or 4+ years with a PhD in Computer Science/Data Engineering Join the team and be a part of the cutting-edge innovation in AI and ML applications.,