ML Engineer role: 

• 10+ years’ experience
• Work and collaborate with data science and engineering teams to deploy and scale models and algorithms.
• Operationalize complex machine learning models into production including end to end deployment.
• Understand standard Machine Learning algorithms (Regression, Classification) & Natural Language processing concepts (sentiment generation, topic modeling, TFIDF) .
• Working knowledge of standard ML packages like scikit learn, vader sentiment, pandas, pyspark.
• Design, Develop and maintain adaptable data pipelines to maintain use case specific data.
• Integrate ML use cases in business pipelines & work closely with upstream & downstream teams to ensure smooth handshake of information.
• Develop & maintain pipelines to generate & publish model performance metrics that can be utilized by Model owners for Model Risk Oversight’s model review cadence.
• Support the operationalized models and develop runbooks for maintenance.

Job Type: Full-time
Pay: $107,664.00 - $120,000.00 per year

Schedule:

• 8 hour shift
• Monday to Friday

Experience:

• MLOps: 10 years (Required)
• scikit learn: 10 years (Required)

Work Location: In perso

• 10+ years’ experience
• Work and collaborate with data science and engineering teams to deploy and scale models and algorithms.
• Operationalize complex machine learning models into production including end to end deployment.
• Understand standard Machine Learning algorithms (Regression, Classification) & Natural Language processing concepts (sentiment generation, topic modeling, TFIDF) .
• Working knowledge of standard ML packages like scikit learn, vader sentiment, pandas, pyspark.
• Design, Develop and maintain adaptable data pipelines to maintain use case specific data.
• Integrate ML use cases in business pipelines & work closely with upstream & downstream teams to ensure smooth handshake of information.
• Develop & maintain pipelines to generate & publish model performance metrics that can be utilized by Model owners for Model Risk Oversight’s model review cadence.
• Support the operationalized models and develop runbooks for maintenance