Marlabs LLC
Client:
AT&T
Base pay range:
$80,000.00/yr - $80,000.00/yr
Primarily looking for Data Bricks, Azure, Mongo DB, SQL Indexing, Python OOPS for modularizing notebooks into python library. Lastly LLM fine tuning using LORA and QLORA.
Responsibilities and Qualifications
Competent Data Scientist, who is independent, results driven and is capable of taking business requirements and building out the technologies to generate statistically sound analysis and production grade ML models.
DS skills with GenAI and LLM Knowledge.
Experience building H2O models (XGboost, logistic regression, neural networks, random forest).
Experience with MongoDB and NO-SQL Datasets.
Experience in Hadoop ecosystem, Databricks and Pyspark.
Expertise in Python/Spark and their related libraries and frameworks.
Experience in building training ML pipelines and efforts involved in ML Model deployment.
Experience in other ML concepts – Real time distributed model inferencing pipeline, Champion/Challenger framework, A/B Testing, Model
Unix/Linux expertise; comfortable with Linux operating system and Shell Scripting.
Familiar with DS/ML Production implementation.
Excellent problem-solving skills, with attention to detail, focus on quality and timely delivery of assigned tasks.
Azure cloud and Databricks prior knowledge will be a big plus.
Seniority Level Mid-Senior level
Employment Type Full-time
Job Function Information Technology
Industries IT Services and IT Consulting
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AT&T
Base pay range:
$80,000.00/yr - $80,000.00/yr
Primarily looking for Data Bricks, Azure, Mongo DB, SQL Indexing, Python OOPS for modularizing notebooks into python library. Lastly LLM fine tuning using LORA and QLORA.
Responsibilities and Qualifications
Competent Data Scientist, who is independent, results driven and is capable of taking business requirements and building out the technologies to generate statistically sound analysis and production grade ML models.
DS skills with GenAI and LLM Knowledge.
Experience building H2O models (XGboost, logistic regression, neural networks, random forest).
Experience with MongoDB and NO-SQL Datasets.
Experience in Hadoop ecosystem, Databricks and Pyspark.
Expertise in Python/Spark and their related libraries and frameworks.
Experience in building training ML pipelines and efforts involved in ML Model deployment.
Experience in other ML concepts – Real time distributed model inferencing pipeline, Champion/Challenger framework, A/B Testing, Model
Unix/Linux expertise; comfortable with Linux operating system and Shell Scripting.
Familiar with DS/ML Production implementation.
Excellent problem-solving skills, with attention to detail, focus on quality and timely delivery of assigned tasks.
Azure cloud and Databricks prior knowledge will be a big plus.
Seniority Level Mid-Senior level
Employment Type Full-time
Job Function Information Technology
Industries IT Services and IT Consulting
#J-18808-Ljbffr