Description :

About the Company :

USEReady helps businesses become self-reliant on data through modern analytics and AI-driven solutions. With rapid growth and a strong focus on innovation, USEReady enables enterprises to modernize BI environments, improve data quality, and adopt cloud-first and AI-driven architectures. The company works with leading technology partners and serves industries including financial services, healthcare, manufacturing, government, education, and retail.

Role Summary :

We are seeking a Machine Learning Engineer with hands-on experience in building, optimizing, and deploying machine learning systems. The role involves designing and implementing intelligent solutions that support enterprise-scale analytics and AI use cases. The ML Engineer will contribute to model development, enhancement of ML workflows, and implementation of AI-powered capabilities that deliver measurable business outcomes.

Key Roles and Responsibilities :

- Design, develop, and implement machine learning solutions using established and advanced ML techniques

- Build, optimize, and manage embedding models to support use cases such as semantic search, recommendations, and contextual intelligence

- Develop and deploy AI agents to enable intelligent automation and decision-making workflows

- Design and implement Retrieval-Augmented Generation (RAG) systems for enterprise applications

- Fine-tune machine learning and language models to improve performance and domain relevance

- Integrate machine learning models with enterprise applications, APIs, and data pipelines

- Ensure reliability, scalability, and performance of ML systems in production environments

- Implement monitoring and governance mechanisms to track model performance and ensure responsible AI usage

- Collaborate with cross-functional teams to translate business requirements into effective ML solutions

- Participate in code reviews, documentation, and knowledge-sharing activities to maintain engineering best practices

Requirements / Qualifications :

- 2- 4 years of hands-on experience in machine learning engineering or applied AI roles

- Strong understanding of machine learning concepts, model training, evaluation, and optimization

- Practical experience working with embedding models and natural language processing techniques

- Experience developing and integrating AI agents into production systems

- Hands-on exposure to Retrieval-Augmented Generation (RAG) architectures

- Experience integrating ML solutions with data pipelines and enterprise systems

- Knowledge of implementing monitoring, observability, and governance for ML models

- Strong SQL skills and experience working with structured datasets

- Ability to collaborate effectively with engineering, analytics, and business teams

- Experience using Snowflake for analytics or data warehousing is preferred

Preferred Skills :

- Familiarity with modern AI and machine learning frameworks

- Understanding of the end-to-end ML lifecycle, including training, deployment, monitoring, and maintenance

- Experience working in cloud-based environments for ML model deployment