Lead AI Engineer

The Lead Machine Learning Engineer is responsible for designing, developing, testing and operationalizing ML (Machine Learning) and other data solutions, including cloud-based or internet-related tools for internal or external consumption. The Incumbent will provide technical solutions to enable the company to meet its strategic objectives through effective collaboration with business analysts, data scientists, software engineers, platform engineers, quality assurance testers, and project managers. The Incumbent will collaborate with others to ensure successful teamwork, effective development, and delivery of high-quality machine learning and data solutions that include MLOps practices such as CI/CD pipelines, automated testing, and monitoring. Oversee the design, development, and deployment of machine learning models and other data solutions in alignment with business requirements and technical specifications defined Guide the training, validation, and optimize machine learning models and other data solutions to ensure high performance and accuracy. Implement techniques for model/solution improvement and fine-tuning. Provide strategic direction in the writing of high-quality, maintainable, and scalable code Expert in Creating and maintaining technical documentation including model development processes, deployment workflows, operational procedures, code comments, design documents, and user manuals MLOps Implementation: Provide expert guidance through the development and implementation of CI/CD pipelines for seamless model deployment. Guide testing throughout the development, integration, deployment, and management of the software solution, and automating where possible to ensure solution quality and security in accordance with industry standards and company policies Foster cross functional collaboration with data scientists, business analysts, software engineers, IT operations, quality assurance testers, and project managers to to translate business requirements into successful technical solutions that are integrated into production environments Provide ongoing solution support including incident and problem management, root cause analysis, request fulfilment, security compliance, fault repair, resiliency testing, and observability Innovation and Research: Stay updated with the latest advancements in machine learning and MLOps practices. Explore and implement innovative solutions to enhance the company's machine learning capabilities. This position can be remote. This position is not eligible for sponsorship for work authorization now or in the future, including conversion to H1-B visa. Must be legally authorized to work in the country of employment without needing sponsorship for employment work visa status now or in the future. Job duties include contact with other employees and access confidential and proprietary information and/or other items of value, and such access may be supervised or unsupervised. The Company therefore has determined that a review of criminal history is necessary to protect the business and its operations and reputation and is necessary to protect the safety of the Company's staff, employees, and business relationships. Education and Experience Required Bachelor's Degree in Computer Science or Computer Engineering or in lieu of a degree, at least 9 years of experience in software development 6+ years of experience in ML, MLOps, and/or software developmen Highly proficient knowledge of software development life cycle (SDLC) methodologies and practices, particularly MLOps and DevOps Highly proficient knowledge of software development tools, platforms and languages, particularly cloud platforms Proven experience in developing, integrating, testing and deploying software solutions for cloud-based or internet-related tools Expert of relational databases and SQL Excellent written and verbal communication skills Proven experience in developing Microservices and in-depth knowledge of various Integration patterns Use of Generative AI tools for SDLC, such as Claude Code, Codex, or Github Copilot Experience developing Generative AI systems, such as LLM-based chatbots, RAG systems, agentic workflows, or the like. Database Management Systems Data Science or Statistics experience, particularly as relates to Machine Learning Programming Languages, particularly Python or R Cloud Technologies & Platforms Software Development Lifecyle (SDLC) Methodology Continuous Integration and Continuous Deployment (CI/CD) Web Services & APIs Familiarity with MLOps practices, including CI/CD pipelines, automated testing, and model monitoring. Experience with tools such as Docker, Kubernetes, Jenkins, and MLflow Containerization and cloud-native development Source Control Systems, particularly github Build Tools and Compilers Software Testing & Quality Assurance Methodologies & Tools Automated Testing Tools Solution Architecture Patterns Data Science platforms Systems Integration patterns and technologies Must be legally authorized to work in the United States without sponsorship now or in the future for employment visa status Must be at least eighteen (18) years of age Preferred Certified Software Development Professional (CSDP) or equivalent certification