Gen AI Engineer Associate - DPS Labs

Overview

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Data scientist

Overall Years Of Experience 3 To 4 Years

Relevant Years of Experience 3+

Data scientist:

Data scientist required to undertake projects to discover the information hidden in vast amounts of data and help us make smarter decisions to deliver even better products. The primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.

Position Summary

• 3+yrs of experience in a similar profile with experience in design and development of machine learning solutions.
• Contribute to products or tools built on Artificial Intelligence technologies and paradigms, that can enable high-value offerings.
• Plan and implement version control of source control
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab. Excellence in at least one of these is highly desirable
• Great communication skills
• Proficiency in using query languages such as SQL, Hive.
• Experience with NoSQL databases, such as MongoDB, Cassandra, HBase {{depending on project needs}}
• Good applied statistics skills, such as distributions, statistical testing, regression, etc
• Good scripting and programming skills
• Strong command on verbal and written English language
  
  

• Solid understanding of deep learning architectures and algorithms
• Experience solving problems in industry using deep learning methods such as recurrent neural networks (RNN, LSTM), convolutional neural nets, auto-encoders etc
• Should have experience of 2-3 production implementation of machine learning projects and Gen AI/Agentic AI projects .
• Knowledge of open source libraries such as Keras, Tensor Flow, Pytorch
• Knowledge and experience in LLMs in developing Gen AI and Agentic AI based solutions.
• Experience in Langchain, Langraph, Autogen/Semantic Kernal/Microsoft Agent framework.
• Knowledge of image processing and computer vision algorithms and libraries such as OpenCV and scikit-image
• Selecting features, building and optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Extending company’s data with third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner
• Should be able to work with a multi culture global teams and team virtually
• Should be able to build strong relationship with project stakeholders
• Should be able to build strong relationship with project stakeholders
  
  

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