Big Data and Machine Learning Expert for full time for 6-12 months
Budget: $1,000 – $3,500 USD
In your Bid please mention the Monthly salary that you would like to get for full-time per month.
We're seeking someone who:
• Has minimum 5 years of experience building Machine Learning models and workflows (TensorFlow, etc. a plus)
• Knows how to get data from a relational database with SQL and is fluent in working with it in Python
• Understands the fundamental and unique challenges behind productionizing algorithms learned from data.
• Can learn and communicate how to fit their knowledge in machine learning to a complex and evolving product
• Applied machine learning (e.g. libSVM, Shogun, Scikit-learn or similar)
• Knowledgeable about data management concepts and have worked with one or more data processing frameworks like Apache Beam, Spark, Flink, and in a cloud environment, like GCP, AWS.
• Experience developing/deploying ML solutions in a public cloud (AWS/Azure/Google Cloud) platforms
•
• Has a Bachelor's degree or equivalent real-world experience, preferably in a related field (Engineering, Computer Science, Statistics, Applied Math)
• Is always willing to learn and apply new techniques where appropriate
• Distributed computing platforms, such as Hadoop (Hive, HBase, Pig), Spark, GraphLab
• Databases (traditional and noSQL)
•
Bonus Points if you have:
• Experience with a mass-market consumer-facing product
• Familiarity with auto-differentiation libraries (e.g., TensorFlow, PyTorch, etc.)
• Proficiency with the pydata stack (NumPy, scipy, pandas)
• Familiarity with scheduling and orchestration tools (e.g., Airflow, Metaflow, etc.)
• Familiarity with AWS services (e.g., SageMaker, S3, EC2, etc.)
We're seeking someone who:
• Has minimum 5 years of experience building Machine Learning models and workflows (TensorFlow, etc. a plus)
• Knows how to get data from a relational database with SQL and is fluent in working with it in Python
• Understands the fundamental and unique challenges behind productionizing algorithms learned from data.
• Can learn and communicate how to fit their knowledge in machine learning to a complex and evolving product
• Applied machine learning (e.g. libSVM, Shogun, Scikit-learn or similar)
• Knowledgeable about data management concepts and have worked with one or more data processing frameworks like Apache Beam, Spark, Flink, and in a cloud environment, like GCP, AWS.
• Experience developing/deploying ML solutions in a public cloud (AWS/Azure/Google Cloud) platforms
•
• Has a Bachelor's degree or equivalent real-world experience, preferably in a related field (Engineering, Computer Science, Statistics, Applied Math)
• Is always willing to learn and apply new techniques where appropriate
• Distributed computing platforms, such as Hadoop (Hive, HBase, Pig), Spark, GraphLab
• Databases (traditional and noSQL)
•
Bonus Points if you have:
• Experience with a mass-market consumer-facing product
• Familiarity with auto-differentiation libraries (e.g., TensorFlow, PyTorch, etc.)
• Proficiency with the pydata stack (NumPy, scipy, pandas)
• Familiarity with scheduling and orchestration tools (e.g., Airflow, Metaflow, etc.)
• Familiarity with AWS services (e.g., SageMaker, S3, EC2, etc.)