AI Solutions Architect / Machine Learning Engineer / Data Science Lead

• *Role Overview:** • *These roles focus on designing, developing, and deploying AI-driven solutions to solve complex business problems. The AI Solutions Architect oversees the architecture and implementation of AI systems, the Machine Learning Engineer develops and optimizes ML models, and the Data Science Lead manages data science initiatives and teams to deliver actionable insights.** • *Key Responsibilities:** • *AI Solutions Architect:** • Design scalable, secure, and high-performance AI/ML solutions aligned with business needs. • Collaborate with stakeholders to understand requirements and translate them into technical architecture. • Evaluate and select AI frameworks, platforms, and tools for implementation. • Ensure compliance with data governance, security, and AI ethics standards. • Guide development teams in implementing AI solutions effectively. • *Machine Learning Engineer:** • Develop, train, and deploy machine learning models using structured and unstructured data. • Optimize model performance through tuning, validation, and testing. • Collaborate with data engineers and AI architects to integrate ML models into production systems. • Maintain reproducible pipelines and documentation for ML workflows. • Stay updated with emerging ML techniques and frameworks. • *Data Science Lead:** • Lead a team of data scientists and analysts to deliver AI/ML projects. • Define project scopes, timelines, and deliverables. • Translate complex data insights into actionable business recommendations. • Mentor team members and ensure adherence to best practices in data science. • Collaborate with business units and IT teams to implement data-driven solutions. • *Shared Responsibilities:** • Develop AI/ML solutions that enhance business operations, decision-making, and customer experiences. • Ensure data quality, security, and integrity across AI initiatives. • Maintain documentation, model versioning, and reproducibility of AI workflows. • Monitor AI solution performance and recommend improvements. • Research and implement emerging AI technologies and tools. • *Qualifications & Skills:** • **Education:**

Bachelor’s or Master’s degree in Artificial Intelligence, Data Science, Computer Science, Statistics, or related field. • **Experience:**

AI Solutions Architect: 7–12 years in AI/ML solution design and implementation. • Machine Learning Engineer: 3–7 years developing and deploying ML models. • Data Science Lead: 5–10 years in data science, managing projects and teams. • **Technical Skills:**

Proficiency in Python, R, or similar programming languages. • Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) and data platforms. • Knowledge of cloud AI platforms (AWS SageMaker, Azure ML, Google AI). • Familiarity with big data tools (Spark, Hadoop) and database systems (SQL, NoSQL). • Strong understanding of model evaluation, validation, and deployment best practices. • **Soft Skills:**

Leadership and team management abilities. • Strategic thinking and problem-solving skills. • Strong communication and stakeholder management skills. • Analytical mindset with attention to detail and quality. • *Work Environment:**

Office-based, hybrid, or remote-friendly, collaborating with AI teams, IT, and business stakeholders. The role involves AI solution architecture, ML model development, data analysis, and team leadership.