AI/ML Engineer

Role Overview: As an AI/ML Architect, your primary role will involve designing the architecture and total solutions for data ingestion, pipeline, data preparation, and orchestration. You will be responsible for applying appropriate machine learning algorithms to the data stream for making predictions. Your hands-on programming skills and architectural capabilities in Python, Java, R, or SCALA will be crucial for this role. Key Responsibilities: - Designing architecture and total solutions from requirements analysis to engineering for data ingestion, pipeline, and data preparation - Applying the right machine learning algorithms on the data stream for predictions - Implementing and deploying machine learning solutions using various models such as Linear/Logistic Regression, Support Vector Machines, Neural Networks, Hidden Markov Models, etc. - Utilizing statistical packages and machine learning libraries like R, Python scikit-learn, Spark MLlib, etc. - Conducting effective data exploration and visualization using tools like Excel, Power BI, Tableau, Qlik, etc. - Performing statistical analysis and modeling including distributions, hypothesis testing, and probability theory - Working with RDBMS, NoSQL, and big data stores like Elastic, Cassandra, Hbase, Hive, HDFS, and other relevant open-source systems - Developing best practices and recommendations for machine learning life-cycle capabilities such as Data collection, Feature Engineering, Model Management, MLOps, Model Deployment, and Model monitoring and tuning Qualifications Required: - Bachelor's degree or equivalent - Minimum 4-6 years of work experience as an Engineer or Architect in a related field Role Overview: As an AI/ML Architect, your primary role will involve designing the architecture and total solutions for data ingestion, pipeline, data preparation, and orchestration. You will be responsible for applying appropriate machine learning algorithms to the data stream for making predictions. Your hands-on programming skills and architectural capabilities in Python, Java, R, or SCALA will be crucial for this role. Key Responsibilities: - Designing architecture and total solutions from requirements analysis to engineering for data ingestion, pipeline, and data preparation - Applying the right machine learning algorithms on the data stream for predictions - Implementing and deploying machine learning solutions using various models such as Linear/Logistic Regression, Support Vector Machines, Neural Networks, Hidden Markov Models, etc. - Utilizing statistical packages and machine learning libraries like R, Python scikit-learn, Spark MLlib, etc. - Conducting effective data exploration and visualization using tools like Excel, Power BI, Tableau, Qlik, etc. - Performing statistical analysis and modeling including distributions, hypothesis testing, and probability theory - Working with RDBMS, NoSQL, and big data stores like Elastic, Cassandra, Hbase, Hive, HDFS, and other relevant open-source systems - Developing best practices and recommendations for machine learning life-cycle capabilities such as Data collection, Feature Engineering, Model Management, MLOps, Model Deployment, and Model monitoring and tuning Qualifications Required: - Bachelor's degree or equivalent - Minimum 4-6 years of work experience as an Engineer or Architect in a related field