Machine Learning Engineer

Company Description Ashiven Infotech Inc. is a technology company specializing in diverse software applications and modern technology stacks, enabling support for multiple business segments. The organization provides end-to-end software consulting and development services, from initial concept and architecture through implementation and long-term maintenance. Team members collaborate with clients to design scalable, efficient solutions tailored to specific business needs. Ashiven’s focus on comprehensive lifecycle support offers professionals the opportunity to work on impactful, long-running technology initiatives.

Role Description This full-time remote Machine Learning Engineer role involves designing, developing, and deploying machine learning models and algorithms to solve complex business problems. The individual in this role will work closely with cross-functional teams to gather requirements, prepare and analyze data, build and train models, and integrate ML solutions into production systems. Daily responsibilities include experimenting with different model architectures, optimizing performance, monitoring deployed models, and documenting technical approaches and outcomes. The role also includes collaborating on code reviews, maintaining high-quality engineering standards, and staying current with emerging ML techniques and tools to continuously improve Ashiven’s solutions.

Qualifications

• Strong foundation in Computer Science and Algorithms, with the ability to design efficient, scalable solutions.
• Applied experience in Neural Networks and Pattern Recognition for real-world machine learning tasks.
• Solid knowledge of Statistics to support feature engineering, model evaluation, and experimental design.
• Proficiency in at least one programming language commonly used in ML (e.g., Python, Java, or C++), and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience working with data pipelines, SQL and NoSQL databases, and cloud platforms (e.g., AWS, Azure, or GCP).
• Ability to translate business requirements into technical solutions, with clear documentation and communication skills.
• Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
• Prior experience in building, deploying, and maintaining machine learning models in production environments is highly beneficial.