Wattmonk Technologies - Anywhere in India/Multiple Locations - Wattmonk Technologies Pvt. Ltd.

Description

• Define, design, and deliver ML architecture patterns operable in native and hybrid cloud architectures.
• Research, analyze, recommend, and select technical approaches to address challenging development and data integration problems related to ML model training and deployment in enterprise applications.
• Perform research activities to identify emerging technologies and trends that may affect the Data Science/ML lifecycle management in the enterprise application portfolio.
• Lead total solution design from requirements analysis, design, and engineering for data ingestion, pipeline, data preparation & orchestration, applying the right ML algorithms on the data stream and predictions.

• Handson programming and architecture capabilities in Python, Java, R, or Scala.
• Minimum 8+ years of experience in enterprise applications development.
• Experience in 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, Mechanism Design, etc.
• Strong handson experience with statistical packages and ML libraries (e.g., R, Python scikitlearn, Spark MLlib, etc.).
• Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.).
• Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.).
• Handson experience in RDBMS, NoSQL, big data stores like Elastic, Cassandra, HBase, Hive, HDFS.
• Work experience as a Solution Architect/Software Architect/Technical Lead.
• Experience with opensource software.
• Excellent problemsolving skills and ability to break down complexity.
• Demonstrated technical expertise around architecting solutions around AI, ML, deep learning, and related technologies.
• Developing AI/ML models in realworld environments and integrating AI/ML using Cloudnative or hybrid technologies into largescale enterprise applications.
• Indepth experience in AI/ML and Data analytics services offered on Amazon Web Services and/or Microsoft Azure cloud solutions and their interdependencies.
• Specializes in at least one of the AI/ML stack (Frameworks and tools like MxNET and TensorFlow, ML platforms such as Amazon SageMaker for data scientists, APIdriven AI Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call).
• Demonstrated experience developing best practices and recommendations around tools/technologies for ML lifecycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches, and Model monitoring and tuning.