Machine Learning Principal Architect, Smarsh

• The ideal candidate will have a deep understanding of advanced machine learning techniques, experience in deploying ML models in production, and a strong track record of leading ML projects from concept to deployment
• Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field
• Experience in machine learning, data science, or related fields
• Proven experience in leading the development and deployment of large-scale ML systems
• Strong background in statistical modeling, data mining, and machine learning algorithms
• Proficiency in programming languages such as Python and Java/Kotlin
• Extensive experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and deploying ML models in a cloud environment
• Strong understanding of data pipelines, ETL processes, and big data technologies
• Excellent problem-solving and analytical skills
• Strong leadership and team management capabilities
• Exceptional communication and collaboration skills
• Ability to work in a fast-paced, dynamic environment

Desirable

• We are seeking a highly skilled and experienced Machine Learning Principal Architect to lead the design, development, and deployment of innovative machine learning solutions across our organization
• This role will focus on driving strategic ML initiatives, shaping the overall architecture, and ensuring that the machine learning models and systems are scalable, reliable, and optimized for performance
• Lead the design and development of scalable, high-performance machine learning architectures that align with business goals
• Define and implement best practices for ML model development, deployment, and maintenance
• Ensure that ML systems are robust, scalable, and secure
• Drive the strategic vision for machine learning within the organization
• Collaborate with stakeholders to understand business needs and translate them into ML solutions
• Stay updated on the latest ML technologies and frameworks to ensure the company remains at the forefront of innovation
• Oversee the end-to-end process of testing, deploying, and monitoring ML models
• Work closely with data scientists, data engineers, and software engineers to integrate ML models into production systems
• Ensure models are optimized for performance, scalability, and cost-efficiency
• Lead and mentor a team of machine learning engineers and data scientists
• Foster a culture of continuous learning and innovation within the ML team
• Provide technical guidance and support to team members on complex ML challenges
• Collaborate with cross-functional teams, including product managers, data engineers, and business analysts, to deliver ML solutions that drive business value
• Communicate technical concepts and the value of ML solutions to non-technical stakeholders
• Ensure that all ML models and processes comply with industry standards, regulations, and ethical guidelines
• Promote the responsible use of AI and machine learning within the organization