AI/ML Engineer

- Lead the comprehensive AI/ML solution lifecycle: defining problems, exploring data, ingesting data, engineering features, developing models, training and tuning, evaluating outcomes, deploying solutions, monitoring performance, and iterating as needed. - Architect and construct scalable production environments for ML/AI, including building model-serving architectures, inference pipelines, microservices/APIs, and implementing CI/CD for machine learning (MLOps), along with performance monitoring and alerts. - Engage with extensive and complex datasets (structured, semi-structured, unstructured) to extract features and insights using advanced ML/AI methods (e.g., deep learning, natural language processing, computer vision, generative models, reinforcement learning). - Select suitable algorithms and frameworks (supervised, unsupervised, deep neural networks, transformer architectures) and implement, fine-tune, and optimize solutions for latency, throughput, cost, accuracy, and robustness/bias. - Deploy solutions in production environments, whether in the cloud or on-premises, while ensuring reliability, scale, high availability, and adhering to security/compliance measures. - Define and instill MLOps best practices, including model versioning, reproducibility, automated training pipelines, drift monitoring, and retraining strategies. - Act as a technical leader and mentor for AI/ML engineers and data scientists, conducting code and design reviews, setting engineering and modeling standards, and sharing industry best practices. - Collaborate across various functions, including product management, engineering, architecture, and operations, to align the AI roadmap with both business needs and technical strategy. - Stay abreast of emerging AI/ML research, tools, and frameworks, promoting their adoption where advantageous; evaluate new platforms, prototype proofs-of-concept, and advocate for innovative solutions. - Clearly communicate technical concepts and AI/ML outcomes to non-technical stakeholders and business leaders, translating findings into actionable business insights.