Azure Mlops Engineer

EnerSys is the global leader in stored energy solutions for industrial applications. We have over thirty manufacturing and assembly plants worldwide servicing over 10,000 customers in more than 100 countries. Worldwide headquarters are located in Reading, PA, USA with regional headquarters in Europe and Asia. We complement our extensive line of Motive Power and Energy Systems with a full range of integrated services and systems. With sales and service locations throughout the world, and over 100 years of battery experience, EnerSys is the power/full solution for stored DC power products.

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Job Purpose

EnerSys the world leader in stored energy and DC power solutions for industrial applications. With electric vehicles (EVs) expected to be nearly 30% of new vehicle sales in few years, electric mobility is becoming a reality, and its mass adoption will require significant buildout of charging infrastructure combining battery storage. EnerSys is well positioned to play a key role with its global footprint and expertise as a leader in DC Fast chargers. Come work alongside some of the most accomplished minds in the industry If you are driven to create a better, more sustainable future, then this is the right place for you.

Essential Duties and Responsibilities

• Develop and maintain cloud based MLOps infrastructure using Azure Machine Learning.

• Automate and enhance development processes to improve code quality and release efficiency.

• Collaborate with cross-functional teams to deploy, monitor, and maintain ML models in production.

• Create and manage ETL/ELT pipelines for data ingestion from various sources.

• Implement and maintain monitoring tools for data pipelines and ML model performance.

• Integrate ML models into CI/CD pipelines, ensuring consistent versioning and testing.

• Contribute to the development of automated MLOps pipelines.

• Stay updated on the latest ML and MLOps tools and practices.

Qualifications

• Bachelor's/Master's degree in Computer Science or a related technical field.

• 2+ years of hands-on experience with Python.

• In-depth knowledge of Azure DevOps services, including Azure Pipelines, Azure Machine Learning, Azure Artifacts, Azure Cloud, Azure Databricks, and other Azure platforms

• 1-2 years of experience with designing, implementing, and maintaining CI/CD pipelines for Machine Learning.

• Experience with object-oriented/scripting languages (Python, Java, C++, etc.).

• Familiarity with networking concepts and distributed computing concepts

• · Experience in data handling, transformation, and management using ETL/ELT processes.

• · Experience in Azure cloud environments, including Kubernetes, compute clusters, compute instances, VMs, Dockers, Azure infrastructure, such as Azure Resource Manager (ARM) templates, virtual networks, and storage solutions.

• · Collaboration skills with the ability to work in a team.

• · Proven ability to work independently, communicate effectively, and drive projects with minimal supervision.

Preferred Qualifications

• Experience with other cloud platforms such as AWS, GCP, or other cloud services.

• Experience with MLOps for different types of ML models, such as Time-Series Forecasts, Regressions, Deep Learning Models, LLMs, GANs, etc.

• Familiarity with DevOps principles and Agile methodologies.

• Experience with data handling, data manipulation and data analysis using platforms like SQL, Python, Azure Databricks, etc.

• Previous experience in Root Cause Analysis (RCA) for application and infrastructure issues.

• Contributions to open-source projects or relevant certifications (e.g., Azure Certified DevOps Engineer) are a plus.

General Job Requirements

• This position will work in an office setting, expect minimal physical demands.

• Must be able to lift 25 pounds/11.5 kilos on occasions.

EnerSys provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. EEO/Minority/Female/Vets/Disabled

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