Engineering Manager - Machine Learning

As a ML Engineering Manager at iMerit, you will play a crucial role in leading and mentoring a team of machine learning and computer vision engineers. Your responsibilities will include fostering a collaborative environment that encourages innovation and continuous improvement. You will oversee the design, development, and deployment of machine learning models, ensuring adherence to best software/ML development practices, coding standards, and quality assurance processes. Additionally, you will be responsible for the productionization of scalable ML solutions, evaluating and selecting appropriate tools, frameworks, and technologies, and participating in architecture, design, and code reviews. Your role will also involve monitoring project progress, identifying risks, and implementing mitigation strategies to ensure timely delivery of projects while meeting quality standards and budget constraints. Furthermore, you will align machine learning initiatives with the company's strategic goals, identify opportunities for leveraging ML to create business value, and contribute to technology roadmaps and long-term planning. Collaboration is key in this role, as you will work closely with other engineering teams, data analysts, and business stakeholders to define problem statements and operationalize solutions. You will facilitate communication and collaboration across teams and departments, representing the team in cross-functional meetings and executive briefings. Qualifications Required: - 12+ years of work experience with a solid background in software engineering and machine learning. - Minimum 7 years of experience in machine learning with at least 5 years in a leadership or managerial role. At least 3 years of experience in building production-grade scalable ML pipelines. - Advanced proficiency in Python and ML frameworks like Tensorflow, Keras, Scikit-learn, or PyTorch. Proficiency in a system language such as Rust, C++, or Java would be an advantage. - Proven ability to deliver a shippable solution given conflicting and ambiguous requirements. - Experience with cloud build, deployment, and orchestration tools. - Experience with MLOps tools and frameworks. - Experience with DevOps, Big Data, and Cloud platforms is a big plus. - Demonstrable analytical and debugging skills. - Excellent communication and interpersonal skills. - In-depth awareness of the latest technologies and trends in Generative AI would be an advantage. - Self-motivated, with an ability and in learning new technologies and adapting quickly to new requirements and environments.,