Company Description Egotechworld is a technology-focused organization that serves as a trusted partner for clients seeking modern IT solutions and industry insights. The company offers opportunities to work with cutting-edge tools and platforms, supporting both business innovation and professional growth. Team members can gain hands-on experience while contributing to practical solutions and engaging with educational tech content. Egotechworld values curiosity, continuous learning, and collaboration across disciplines to deliver meaningful results. The environment is designed for individuals who want to build their expertise while helping shape future technology trends.
Role Description This is a full-time Machine Learning Engineer role based in the San Francisco Bay Area with a hybrid work arrangement, allowing a mix of on-site and work-from-home days. In this role, you will design, implement, and optimize machine learning models and pipelines to solve real-world problems and improve product features. You will work closely with cross-functional teams to gather requirements, prepare and analyze datasets, select appropriate algorithms, and evaluate model performance. Daily activities include developing production-ready code, conducting experiments, tuning models, and documenting methodologies and results. You will also contribute to code reviews, collaborate on system architecture decisions, and stay current with emerging machine learning techniques and tools to enhance Egotechworld’s technology offerings.
Qualifications
- Strong foundation in Computer Science and Algorithms, with experience implementing efficient and scalable solutions.
- Hands-on experience in Pattern Recognition and Neural Networks, including designing, training, and deploying models.
- Solid understanding of Statistics and probabilistic methods for data analysis, model evaluation, and experimentation.
- Proficiency in at least one programming language commonly used in machine learning (e.g., Python), and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Experience working with large datasets, data preprocessing, and feature engineering in production environments.
- Ability to collaborate in hybrid teams, communicate complex technical ideas clearly, and document work for diverse stakeholders.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
- Experience with cloud platforms (e.g., AWS, GCP, Azure), MLOps practices, and version control (e.g., Git) is highly beneficial.