Job Description
<p><p>We are now looking for highly experienced Senior Engineering Managers who can lead the platform scale and components, and make it the industry best in the relevant components.<br/><br/>Ideal candidates should have at least 5+ years of experience working with products that require heavy engineering and scaling requirements.<br/><br/>Preference is from a product background with strong discipline around the stack and PR quality.</p><p><br/></p><p>Job Description :</p><p><b><br/></b></p><p><b>-</b> 5+ years of experience in building and deploying enterprise-grade machine learning infra, SaaS software, data analytics solutions, or online platforms</p><p> <br/><b>-</b> 2+ years of experience in building LLM infra or high-volume AI inference components.<br/><br/><b>-</b> Academic degree in Computer Science, Engineering, or a related field<br/><br/><b>-</b> Strong background in Python programming, Distributed computing, Engineering, big data processing, and cloud computing (AWS, Azure, GCP, on-premises)<br/><br/><b>-</b> Experience in optimizing, scaling, and reliability of large-scale systems for various data modalities and AI models.<br/><br/><b>-</b> Strong fundamentals and discipline in CI/CD pipelines, containerization (Docker, Kubernetes), and multi-cloud environments.<br/><br/><b>-</b> Proven track record in product management in designing and delivering complex, high-performance solutions for large-scale enterprise customers without faults and the ability to auto-scale the systems through delivering the essential SLAs in production during inference<br/><br/><b>-</b> Programming skills : expert in Python and solid coding practices<br/><br/><b>-</b> Data Engineering : expert in MongoDB and strong fundamentals in data lakes, data storage, ETL pipelines, and building real-time data pipelines.<br/><br/><b>-</b> Strong material skills, excellent communication, collaboration, and leadership skills with the ability to lead teams, mentor juniors, and work with other teams.<br/><br/><b>-</b> Strong system architecture background that supports scaling in regulated industries.<br/><br/><b>-</b> Experience in scaling AI/ML production systems using classic ML models, LLMs, and Deep Learning models on traditional hardware and high-performance computing.</p><p><br/></p><p><b>Roles and responsibilities :</b><br/><br/>As Sr Engineering Manager, you'll be the main SPOC for all the engineering efforts behind the AryaXAI platform, serving customers in SaaS and on-premise modes and scaling multiple AI models in startups, SMEs, and highly regulated industries.</p><p><br/></p><p><b>-</b> You'll be responsible for designing, modifying, and scaling architecture, as well as designing and implementing scalable infrastructure for AI/ML solutions and data engineering.<br/><br/><b>-</b> You'll be the SPOC with the R&D team, collecting the productized components and adding and scaling these components on the platform.<br/><br/><b>-</b> Architect and scale AI inference platform and related components for all data modalities like Tabular, text, image, video, etc.<br/><br/><b>-</b> You'll be responsible for designing the AI Ops and AI Inferencing Ops model building, data preprocessing, model inferencing, explainability, monitoring, alignment, risk management components.<br/><br/><b>-</b> You'll work on running multiple optimizations on inference speed and latencies to serve multiple AI models - LLMs, DL models, classic ML models, etc.<br/><br/><b>-</b> You'll manage product development activities, including scrum reviews and productivity optimization across engineering, as well as collaborate with R&D/data science and front-end teams.<br/><br/><b>-</b> You'll mentor and guide juniors and middle managers.<br/><br/><b>-</b> You'll continuously improve the standards of the product, as well as the architecture, culture, and experience</p><br/></p> (ref:hirist.tech)