ML Engineer

Computer House

۱۴ گھنٹے پہلے شائع ہوئی Report Job

PKR. 200,000 - 200,000/Month

Computer House is seeking a skilled Machine Learning Engineer with a minimum of four years of experience to join our innovative technology team. The successful candidate will be responsible for designing, developing, and deploying advanced machine learning models that enhance our products and services. This role involves working closely with cross-functional teams to understand data requirements, apply data preprocessing techniques, and implement machine learning algorithms that drive business value. The engineer will manage a team of two members, providing guidance and ensuring best practices in model development and deployment are followed. The role requires deep technical knowledge in machine learning, data analysis, and algorithm development, along with strong problem-solving abilities. The candidate will actively participate in the entire machine learning lifecycle, from data collection and cleaning to model tuning and validation. Additionally, the ML Engineer will collaborate with stakeholders to translate business needs into technical solutions and deliver scalable and efficient models that improve operational efficiency and customer experience.
Responsibilities

Develop, test, and deploy machine learning models using appropriate algorithms and data preprocessing techniques.
Manage and mentor a team of two ML engineers, ensuring adherence to technical standards and project timelines.
Collaborate with data engineers and software developers to integrate ML models into production systems.
Analyze large datasets to identify trends, patterns, and insights that can improve model performance and business outcomes.
Optimize and fine-tune machine learning models to enhance accuracy, speed, and scalability.
Stay up to date with the latest machine learning research and technologies, applying relevant innovations to projects.
Design and implement experiments to validate and assess the effectiveness of machine learning solutions.
Document model architectures, workflows, and results for knowledge sharing and reproducibility.
Ensure data quality and perform thorough data preprocessing including cleaning, normalization, and feature engineering.
Communicate progress and technical concepts clearly to both technical and non-technical stakeholders.
Contribute to the continuous improvement of development processes and ML infrastructure at Computer House.