Specialist-Machine Learning Ops

Key Skills

Java Programming, Python Programming, SQL, DevOps, Azure, AWS, Keras software library, PyTorch, TensorFlow, Apache Airflow, Docker, Kubernetes-K8s, Terraform, Kubeflow, DevSecOps, Databricks, IaaS, PaaS

Job Description

If you desire to be part of something special, to be part of a winning team, to be part of a fun team – winning is fun. We are looking forward to a Specialist Machine Learning Ops Engineer based in Pune, India. In Eaton, making our work exciting, engaging, meaningful; ensuring safety, health, wellness; and being a model of inclusion & diversity are already embedded in who we are - it’s in our values, part of our vision, and our clearly defined aspirational goals. This exciting role offers opportunity to:

Our Centre for Intelligent Power located at Eaton’s global headquarters in Dublin, applies data science to transform all aspects of our company. We’re working on solving the technical challenges of today’s digital world, while developing groundbreaking technology that’s going to power the next generation of futuristic products and services. Our multidisciplinary team of data scientists, data engineers and UX/UI designers are developing products based on AI, Edge computing and Machine learning.We’re continuing to expand our organization and are now recruiting a Specialist Machine Learning(ML) Ops Engineer who will support the expansion and management of our large-scale, highly-distributed edge and cloud data processing pipelines.

• Demonstrate exceptional impact in delivering projects, products and/or platforms in terms of scalable data processing and application architectures, technical deliverables and delivery throughout the project lifecycle.
• Responsible for ensuring that ML deployment pipelines can maintain and monitor model accuracy and ensure application code quality.
• Lead the development of the Intelligence layer MLOps pipelines, ensuring that infrastructure and code is delivered incrementally and according to our internal security deployment policies.
• Work with stakeholders, define the deployment strategy and infrastructure to support AI/ML requirements
• Responsible for ensuring model development is deployable and sustainable at scale and meets the business needs.
• Author high-quality, high-performance, unit-tested code to extract and transform data based on business and data science needs
• Must be conversant with Agile methodologies and tools and have a track record of delivering products in a production environment.
• Work directly with stakeholders, engineering, and test to create high quality solutions that solve end-user problems.
• Develop and execute agile work plans for iterative and incremental project delivery
• Explore and recommend new tools and processes which can be leveraged across the data preparation pipeline for capabilities and efficiencies.
• Ensure that our development and deployment are tightly integrated to each other to maximize the deployment user experience.
• Curator for all code and binary artifact repositories (containers, compiled code)

Qualifications

Requirement:

• BE in computer science or equivalent software engineering discipline.
• 10+ years of experience in a relevant and comparable role in the software industry, with a proven track record of success.

• Proficient in Python and Linux environments to support model training, analysis and prediction pipelines for our advanced analytics services.
• Experienced in designing and building highly distributed and scalable Analytics/Data Science/Machine Learning pipeplines hosted in major public and/or private cloud providers such as Azure, AWS or Google Cloud.
• Proficient in developing and maintaining AI & ML DevSecOps pipelines to support Model training and prediction requirements.
• Experience with Docker & Docker orchestration technologies (e.g. Kubernetes (K8S), Docker compose).
• Ability to develop Machine learning and validation pipelines in a secure and enterprise grade environment.
• Strong problem solving and software debugging skills with a track record of delivery and a willingness to roll up sleeves to get the job done.
• Excellent verbal and written communication skills including the ability to effectively explain technical concepts.

Desired:

• Masters or equivalent degree in computer science or comparable software engineering discipline.
• Experience in deployment of Infrastructure-as-Code using Terraform.
• Proficiency with cloud technologies (IaaS, PaaS, serverless technology) micro-service design, CI/CD and DevOps technologies.
• Experience in Knowledge Graphs and integration this technology into intelligence pipelines.
• Experience in building and deploying AI/ML models in large scale production projects with modern light-weight design (API, Microservices etc.)
• Experience with ML frameworks and libraries such as TensorFlow, Keras, Pytorch and Kubeflow.
• Experienced in big data orchestration frameworks such as Apache Airflow.
• Knowledgeable in leveraging data transit protocols and technologies (AMQP, MQTT, Rest API, JDBC, etc).
• Knowledge of multiple cloud and edge technologies, especially Microsoft Azure e.g. Databricks, Azure IoT Edge.
• Knowledge of cloud development platforms such as Azure or AWS and their associated data storage options.
• Experience in integrating Artifact repositories (eg JFrog Artifactory) into CI/CD pipeline to manage and control access to binary dependencies
• Experience with Agile development methodologies and concepts.
• Keeps abreast of upcoming software development/engineering tools, trends, and methodologies.
• Good judgment, time management, and decision-making skills.

Yes! Because you are the one we are looking for, we hope to hear from you now!

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