AI/ML Engineer

Role Overview: As an AI/ML Architect, you will be responsible for architecture design and total solution design from requirements analysis, design, and engineering for data ingestion, pipeline, data preparation & orchestration. You will be applying the right ML algorithms on the data stream and predictions. Your role will involve hands-on programming and architecture capabilities in Python, Java, R, or SCALA. Key Responsibilities: - Implementing and deploying Machine Learning solutions using various models such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, and Mechanism Design. - Demonstrating strong hands-on experience with statistical packages and ML libraries like R, Python scikit learn, Spark MLlib, etc. - Conducting effective data exploration and visualization using tools such as Excel, Power BI, Tableau, and Qlik. - Utilizing extensive background in statistical analysis and modeling including distributions, hypothesis testing, and probability theory. - Hands-on experience in RDBMS, NoSQL, big data stores like Elastic, Cassandra, Hbase, Hive, HDFS, and relevant open-source systems. - Developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches, and Model monitoring and tuning. Qualifications Required: - Bachelors degree or equivalent. - Minimum 4 - 6 years of work experience as an Engineer or Architect. Note: No additional details of the company are provided in the job description. Role Overview: As an AI/ML Architect, you will be responsible for architecture design and total solution design from requirements analysis, design, and engineering for data ingestion, pipeline, data preparation & orchestration. You will be applying the right ML algorithms on the data stream and predictions. Your role will involve hands-on programming and architecture capabilities in Python, Java, R, or SCALA. Key Responsibilities: - Implementing and deploying Machine Learning solutions using various models such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, and Mechanism Design. - Demonstrating strong hands-on experience with statistical packages and ML libraries like R, Python scikit learn, Spark MLlib, etc. - Conducting effective data exploration and visualization using tools such as Excel, Power BI, Tableau, and Qlik. - Utilizing extensive background in statistical analysis and modeling including distributions, hypothesis testing, and probability theory. - Hands-on experience in RDBMS, NoSQL, big data stores like Elastic, Cassandra, Hbase, Hive, HDFS, and relevant open-source systems. - Developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches, and Model monitoring and tuning. Qualifications Required: - Bachelors degree or equivalent. - Minimum 4 - 6 years of work experience as an Engineer or Architect. Note: No additional details of the company are provided in the job description.