Job Location: Bangalore
Bangalore, Karnataka, India
ABOUT UPL:
UPL is focused on emerging as a premier global provider of total crop solutions designed to secure the worldโs long-term food supply. Winning farmers hearts across the globe, while leading the way with innovative products and services that make agriculture sustainable, UPL is the fastest growing company in the industry. UPL has a rich history of 50+ years with presence in 120+ countries. Based on the recognition that humankind is one community, UPLโs overarching commitment is to improve areas of its presence, workplace, and customer engagement.
Our purpose is โOpenAgโ. An Open agriculture network that feeds sustainable growth for all. No limits, no borders.
In order to create sustainable food chain, UPL is now working to build a future-ready, analytics-driven organization that will be even more efficient, more innovative, and more agile. We are setting up โDigital and Analyticsโ CoE to work on some disruptive projects that will have an impact that matters for the planet. It will help us reimagine our business to ensure the best outcomes for growers, consumers, employees, and our planet.
Work with us to get exposure to cutting-edge solutions in digital & advanced analytics, mentorship from senior leaders & domain experts, and access to a great work environment.
JOB RESPONSIBILITIES:
The incumbent in this role would be an Engineer with keen problem-solving skills and are passionate about building scalable production grade infrastructure and automation workflows for production-grade machine learning systems. You have a deep experience in modern, secure infra technologies like cloud and Kubernetes, and scalable data science tooling. Youโll participate in the detailed technical design, development, and implementation of automated machine learning
in a production environment using a combination of best-in-class OSS and vendor technologies. Working within an Agile environment, youโll serve as a technical lead, providing input into machine learning systems decisions, developing and reviewing infra and tooling setup and configuration, and ensuring high availability and performance of our machine learning systems. Your efforts will be critical to successfully set up LiveOps protocols
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Enable data scientists and data engineers to build and productionize and deploy machine learning models by setting up cloud environments and toolings
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Work to set the standards for infra and devops practices within the platform engineering team and support across other disciplines
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Choose and use the right cloud services, devops tooling and ML tooling for the team to be able to produce high-quality code that allows us to put solutions
into production -
Build modern and secure CI/CD pipelines to automate best practices development and deployment workflows used by data scientists (ML pipelines) and data engineers (data pipelines)
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Support, select and shape the next generation of the infra and automation of ML products and platforms
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Bring expertise in cloud to enable ML use case development, including MLOps
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Play an active role in discussions and workshops for use case set-up, deployment, and scaling pilots.
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Promote clean coding practices and embed checks and balances (e.g. code linting) within deployment pipelines
REQUIRED EDUCATION AND EXPERIENCE:
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Bachelorโs degree required; Computer Science, MIS, or Engineering preferred
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5+ years industry experience
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2+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of production-grade Cloud and DevOps applications, preferably solving for multiple teams and use cases
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1+ years of on-the-job experience working with data teams and automating ML and other data-intensive applications development workflows
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Excellent hands-on expert knowledge of cloud platform infrastructure and administration (Azure/AWS/GCP) with strong knowledge of cloud services integration, cloud security and devops stack of at least one major cloud platform
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Expertise setting up CI/CD processes, building and maintaining secure devops pipelines with at least 2 major DevOps stacks (e.g., Azure DevOps, Gitlab, Argo)
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Experience with modern development methods and tooling: Containers (e.g., docker) and container orchestration (K8s), CI/CD tools (e.g., Jenkins, Argo, Azure Devops), version control (Git, Github, Gitlab), orchestration/DAGs tools (e.g., Airflow, Kubeflow)
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Hands-on coding skills Python 3 (e.g., API including automated testing frameworks and libraries
(e.g., pytest) and Infrastructure as Code (e.g., TerraForm) and Kubernetes artifacts (e.g., deployments, operators, helm charts) -
Experience setting up at least one contemporary MLOps tooling (e.g., experiment tracking, model governance, packaging, deployment, feature store)
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Practical knowledge of data science workflow and relevant common tooling for DS (e.g., Jupyter, Kedro) and DE (e.g., Airflow), with being able to build a simple Python-based ML pipeline a huge plus
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Knowledge of SQL (intermediate level or more preferred) and familiarity working with at least one common RDBMS (mySQL, Postgres, SQL Server, Oracle)
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Required: Microsoft Certified: DevOps Engineer Expert or equivalent for AWS/GCP1
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Preferred: Cloud architect, developer, or security certifications for Azure/AWS/GCP1
Location: Bangalore / Mumbai
Whatโs in it for you?
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Disruptive projects: Work on โbreakthroughโ digital-and-analytics projects to enable UPLโs vision of building a future ready organization. It involves deploying solutions to help us increase our sales, sustain our profitability, improve our speed to market, supercharge our R&D efforts, and support the way we work internally. Help us ensure we have access to the best business insights that our data analysis can offer us.
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Cross functional leadership exposure: Work directly under guidance of functional leadership at UPL, on the most critical business problems for the organization (and the industry) today. It will give you exposure to a large cross-functional team (e.g.: spanning manufacturing, procurement, commercial, quality, IT/OT experts), allowing multi-functional learning in D&A deployment
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Environment fostering professional and personal development: Strengthen professional learning in a highly impact-oriented and meritocratic environment that is focused on delivering disproportionate business value through innovative solutions. It will be supported by on-the-job coaching from experienced domain experts, and continuous feedback from a highly motivated and capable set of peers. Comprehensive training programs for continuous development through UPL’s D&A academy will help in accelerating growth opportunities.
Come join us in this transformational journey!
Letโs collectively Change the game with Digital & Analytics!
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