Machine Learning Engineer

Qualification (Educational): Bachelor's or Master's degree in Computer Science, Machine Learning or a related field.

Location City: Chennai

Skill Sets Required:

• Minimum of 3 years of hands-on experience in machine learning and deep learning model development and deployment.
• 3 years+ of experience manipulating data sets and building deep learning models, with a Bachelor's or Master's degree in Statistics, Mathematics, Computer Science or other quantitative field.
• Strong programming experience, with solid understanding of software engineering design patterns and best practices.
• Experience with SQL & NoSQL databases such as MongoDB is an advantage.
• Knowledge of a variety of machine learning techniques (clustering, recommender systems, Natural Language Processing, Deep learning etc.) and their real-world applications.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.).
• Experienced in the use of CI/CD and DevOps tools such as Jira, Jenkins, GIT/Bitbucket.
• Ideally has track record of deploying Machine Learning solutions into Production at scale.
• Experience with containerization technologies (e.g., Docker, Kubernetes).
• Excellent problem-solving skills and the ability to work independently as well as in a collaborative team environment.

Projects: Showcase 2 or more projects involving the development and deployment of machine learning and deep learning models. Highlight the challenges faced, solutions implemented, and the impact of the projects.

Roles & Responsibilities:

Position Overview: As a Machine Learning Engineer at Ramco Systems, you will play a crucial role in developing and implementing advanced machine learning and deep learning models including LLMs. The ideal candidate will have a minimum of 3 years of hands-on experience in machine learning, with a strong focus on deep learning techniques. A background in computer science and a passion for creating intelligent solutions that have a real-world impact are essential.

Responsibilities:

• Implement and deploy machine learning and deep learning models to solve complex business challenges. Conduct exploratory data analysis and feature engineering to extract meaningful insights from large structured & unstructured datasets.
• Evaluate and fine-tune deep learning models, including transformer models, for optimal performance, scalability, and efficiency.
• Stay abreast of the latest advancements in machine learning and deep learning and contribute to the adoption of new technologies within the team.
• Collaborate with data engineers to build and maintain scalable data pipelines for model training and inference.
• Work closely with data scientists and stakeholders to understand project goals and requirements.
• Contribute to the development and maintenance of a robust and scalable machine learning infrastructure