Hyderabad
2 years ago
19 Applied
JOB ID:43419
Job details
Job Type
Full Time
Functional Area
Research/Analytics/Business Intelligence/Big data,Software Development
Industry
FMCG/Food/Consumer Durables
Education
Not Specified
Experience Required
8 - 12 Yrs
Key Skills Required
python, sql, ml ops / devops, scaled agile framework, spark, big data, hadoop, data bricks
Other Skills Required
Job Description
L08- Architect-ML Ops Engineer- PEPIT 283Purpose:
The ML and Data Ops engineer will work in developing advanced analytics, machine learning, artificial
intelligence and business intelligence data engineering projects. Specific scope of this role is to develop data processing solution in support of ML/AI/BI projects using big data and analytics toolsets in a CI/CD environment.
Analytics toolsets may include Spark/Databricks for batch/streaming data, and other big data technologies offered by Microsoft Azure or open source toolsets.
This role will also help automate the end to end cycle with Azure Machine Learning Services and Pipelines.Scope of Measures:
- Delivery of key Advanced Analytics projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope
- Collaborate with Data Scientists/ML engineers to understand data... See More
The ML and Data Ops engineer will work in developing advanced analytics, machine learning, artificial
intelligence and business intelligence data engineering projects. Specific scope of this role is to develop data processing solution in support of ML/AI/BI projects using big data and analytics toolsets in a CI/CD environment.
Analytics toolsets may include Spark/Databricks for batch/streaming data, and other big data technologies offered by Microsoft Azure or open source toolsets.
This role will also help automate the end to end cycle with Azure Machine Learning Services and Pipelines.Scope of Measures:
- Collaboration with CTO development teams, data scientists, data engineers, platform engineers.
- Collaboration with delivery leads.
- Delivery of key Advanced Analytics projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope
- Collaborate with Data Scientists/ML engineers to understand data... See More
L08- Architect-ML Ops Engineer- PEPIT 283Purpose:
The ML and Data Ops engineer will work in developing advanced analytics, machine learning, artificial
intelligence and business intelligence data engineering projects. Specific scope of this role is to develop data processing solution in support of ML/AI/BI projects using big data and analytics toolsets in a CI/CD environment.
Analytics toolsets may include Spark/Databricks for batch/streaming data, and other big data technologies offered by Microsoft Azure or open source toolsets.
This role will also help automate the end to end cycle with Azure Machine Learning Services and Pipelines.Scope of Measures:
- Delivery of key Advanced Analytics projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope
- Collaborate with Data Scientists/ML engineers to understand data and models and leverage various advanced analytics capabilities
- Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards
- Use big data technologies to help process data and build scaled data pipelines (batch to real time)
- Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines leveraging the NGAA platform (Azure)
- Setup cloud alerts, monitors, dashboards and logging and troubleshoot machine learning infrastructure
- Automate ML models deploymentsYears of Experience:
- Overall 8+ years of IT experience
- 5+ years of work experience in a MLOps / DevOps engineer role
- At least 3+ years of experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers (Azure preferred)Mandatory technical skills:
- Experience in Python and SQL is required to build data pipelines
- Knowledge of ML Ops / DevOps is required
- Knowledge of deploying ML models is required
- Possess an intuitive understanding of machine learning algorithms, supervised and unsupervised modeling techniques
- Experience executing and contributing to automation infrastructure
- Exceptional analytical and problem-solving skills
- Should be able to work independently
- Experience supporting and working with cross-functional teams in a dynamic environment
- Prior experience in working in SCALED AGILE framework
- Experience in Spark and PythonNice to Have
• Knowledge and experience in relational databases (Teradata preferred), Data Warehousing and ETL/ELT technologies
• Experience in Big Data technologies including Hadoop, Data Bricks, etcMandatory nontechnical skills:
- Ability to work with virtual teams (remote work locations); lead team of technical resources (employees and contractors) based in multiple locations across geographies
- Participate in ideation and solutioning discussions, driving clarity of complex issues/requirements to build robust solutionsDifferentiating competencies required:
- Strong communication skills to meet with business, understand sometimes ambiguous, needs, and translate to clear, aligned requirements
- Ability to work independently with business partners to understand requirements quickly, perform analysis and determine suitable solutions See Less
The ML and Data Ops engineer will work in developing advanced analytics, machine learning, artificial
intelligence and business intelligence data engineering projects. Specific scope of this role is to develop data processing solution in support of ML/AI/BI projects using big data and analytics toolsets in a CI/CD environment.
Analytics toolsets may include Spark/Databricks for batch/streaming data, and other big data technologies offered by Microsoft Azure or open source toolsets.
This role will also help automate the end to end cycle with Azure Machine Learning Services and Pipelines.Scope of Measures:
- Collaboration with CTO development teams, data scientists, data engineers, platform engineers.
- Collaboration with delivery leads.
- Delivery of key Advanced Analytics projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope
- Collaborate with Data Scientists/ML engineers to understand data and models and leverage various advanced analytics capabilities
- Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards
- Use big data technologies to help process data and build scaled data pipelines (batch to real time)
- Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines leveraging the NGAA platform (Azure)
- Setup cloud alerts, monitors, dashboards and logging and troubleshoot machine learning infrastructure
- Automate ML models deploymentsYears of Experience:
- Overall 8+ years of IT experience
- 5+ years of work experience in a MLOps / DevOps engineer role
- At least 3+ years of experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers (Azure preferred)Mandatory technical skills:
- Experience in Python and SQL is required to build data pipelines
- Knowledge of ML Ops / DevOps is required
- Knowledge of deploying ML models is required
- Possess an intuitive understanding of machine learning algorithms, supervised and unsupervised modeling techniques
- Experience executing and contributing to automation infrastructure
- Exceptional analytical and problem-solving skills
- Should be able to work independently
- Experience supporting and working with cross-functional teams in a dynamic environment
- Prior experience in working in SCALED AGILE framework
- Experience in Spark and PythonNice to Have
• Knowledge and experience in relational databases (Teradata preferred), Data Warehousing and ETL/ELT technologies
• Experience in Big Data technologies including Hadoop, Data Bricks, etcMandatory nontechnical skills:
- Ability to work with virtual teams (remote work locations); lead team of technical resources (employees and contractors) based in multiple locations across geographies
- Participate in ideation and solutioning discussions, driving clarity of complex issues/requirements to build robust solutionsDifferentiating competencies required:
- Strong communication skills to meet with business, understand sometimes ambiguous, needs, and translate to clear, aligned requirements
- Ability to work independently with business partners to understand requirements quickly, perform analysis and determine suitable solutions See Less
About Company
PepsiCo is a global food and beverage leader with a product portfolio including 22 brands that generate more than $1 billion each in annual retail sales. Our main businesses – Quaker, Tropicana, Gatorade, Frito-Lay and Pepsi-Cola make hundreds of enjoyable foods and beverages that are loved throughout the world.
At PepsiCo, you get the best of both worlds: an entrepreneur’s mindset plus reach and resources. Our collaborative culture and worldwide presence generate a stream of new opportunities to define the future and propel your life’s work. Bring your unique perspective. Bring curiosity. Bring ingenuity, and drive. We’ll give you a platform to be daring on a global scale.
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