Job Description & Required Skills
Company Description EgoTECHworld is a trusted technology partner that provides cutting-edge IT solutions to a broad range of clients. The company offers opportunities to gain practical industry experience through real-world projects and collaborative work. Team members also contribute to and benefit from insightful tech articles and resources that highlight current trends and best practices. EgoTECHworld fosters a learning-focused environment where professionals can grow their skills, share knowledge, and help shape innovative digital solutions.
Role Description The Machine Learning Engineer role at EgoTECHworld is a full-time remote position focused on designing, building, and deploying machine learning models for real-world applications. Day-to-day responsibilities include developing and optimizing algorithms, implementing and training neural network architectures, and performing data preprocessing and feature engineering. The role involves collaborating with cross-functional teams to define technical requirements, conducting experiments and performance evaluations, and translating business needs into scalable ML solutions. The Machine Learning Engineer is also expected to document workflows, maintain code quality, and stay current with emerging tools and techniques in machine learning and artificial intelligence.
Qualifications
Strong foundation in Computer Science and Algorithms, including data structures and software engineering best practices.
Experience with Pattern Recognition and Neural Networks for building and improving predictive models.
Proficiency in Statistics and related analytical methods for model evaluation and data-driven decision-making.
Hands-on experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages such as Python.
Ability to work effectively in a remote environment, including strong communication, collaboration, and time-management skills.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
Experience with cloud platforms (e.g., AWS, GCP, Azure), MLOps tools, and deploying models into production is a plus.