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Machine Learning Engineer
3 months ago
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.
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.
Benefits:
- Competitive salary
- Professional development opportunities
- Dynamic and collaborative work environment If you are passionate about machine learning, possess advanced deep learning skills, and thrive in a collaborative environment, we encourage you to apply for this exciting opportunity. Join us in shaping the future of technology and making a meaningful impact with your skills and expertise.
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