| DevOps with Machine Learning DevOps with Machine Learning at Remote, Remote, USA |
| Email: [email protected] |
| Hello, Greetings of the day, My name is Shikha Singh, and I am a Staffing Specialist at Convextech. I am reaching out to you on an exciting job opportunity with one of our clients. No Indian Candidate. DevOps with Machine Learning DevOps with Machine Learning Dallas, TX or Bentonville, AR **FROM DAY 1** 6+ Month Contract Phone then Video **UPDATE - Feedback on candidates: All of the candidates are able to discuss High Level topics but are unable to articulate/communicate deeper when pressed for details and alternative solutions to solve problems. We need someone who is a strong communicator for this role. Please share profiles of folks with exceptional communication skills** **GLIDER Assessment WILL BE REQUIRED** **Candidates must be strong with Google Cloud Platform (GCP), Kubernetes, Grafana, Machine Learning, PySpark. Manager said what would make a candidate stand out if if they have performed Kubernetes implementations and understand the production deployment process on resume* ML model development model. DevOps will be setting up the environment, setting up CICD environment for the platform. Devops engineers will be making sure the platform is up and running. Containerized in kubernetes. Deployment targets, moving into walmart production state. Lots of automation, red tape processes. Is the object performing well ML (How well is it performing, is the data changing) Always looking for areas of improvement and make the environment easier for the devs. Infosec is going to be involved as well. GCP, Google, ML experience (Monitoring) Splunk, Grafana, prometheus. Python experience will be a plus. Code that assits w automation will be needed, need to understand the python code. 6 month contract. Enterprise experience is key. Pyspark, Spark. No writing code, or translating it, thats the engineering devs issues. Resume experience, (tech stack review) How detailed they are, what role did they play in previous implementations, any evidence of an Existing process and made it better. Situational tech questions of a broken system, how can we fix it Large company experience w Kubernetes, Uber, Google, Meta, Amazon, Tesla, ETC. being able to understand all of the intracasies. Automation, CI'CD (setting up and configuring this process) Continual process improvement. GENERIC JOB DESCRIPTION: Our Data Science team is building a first-in-class platform of tools and services covering high-performance computing, ML training services, DevOps, model deployment, and metadata capture. Our goal is to decrease AI/ML development/training cycle time and raise the quality bar on AI/ML's shipped services by drastically simplifying the process of AI/ML Engineering. This is a hands-on position where you will be empowered to be creative, ambitious, and bold. Our mission on the Data Science team is to provide deep computing expertise, automated workflows, production-grade infrastructure, and helpful tooling to enable the AI/ML team and our partners to solve cutting-edge research problems in the retail space and translate their solutions into a direct impact on the business and on members. The ML Engineer function works directly with AI/ML project teams doing cutting-edge work, serving as the voice of expertise in software engineering, scientific computing at scale, and expert problem-solving. Responsibilities o Identifies, creates, and applies software development and security standards and practices. o Plans, designs, and documents software components. o Develops and operates end-to-end automated solutions for IT ops activities (including deployment, release management, monitoring, etc.). o Collaborates with Operations, Development, and QA functions to develop solutions that are predisposed to scalability and simplified maintenance. o Configures and maintains on-premises and Googlecloud infrastructure to ensure availability, performance, scalability, and security of development, testing, and production environments, relying on automated scripts and configuration management tools. o Creates and manages Infrastructure as Code (IaC). o Maintains, extends, and builds automated CI and CD pipelines. o Demonstrates expertise in the deployment of integrated or stand-alone releases across multiple interconnected and dispersed applications. o Uses industry standard tools to improve and speed up delivery of our products and services. o Provides fast and thoughtful issue resolution by executing quick fixes or proactively identifying and solving problems related to builds in production environments. o Creates the pipeline to periodically generate code quality metrics. o Drives each team to be self-sufficient by providing tools and training and brings different teams together to work towards common goals. o Coordinates resources across technology functions to stand up and monitor environments. o Configures and automates development and test environment, deployment, automation, and support test data management. o Establishes workflows that use the automated pipelines for CI and CD. o Works closely with product and application teams to create version control branching strategy. o Works cross-value streams with other DevOps Engineers to avoid and resolve merge conflicts. o Develops tool integrations that allow for end to end traceability for application development (from requirements to code objects changed to meet the requirements). o Develops, maintains, extends and builds automated Continuous Integration and Continuous Delivery pipelines. Required o BS or MS degree in Computer Science or related field o Expertise in software development o Expertise in CI/CD and DevOps practices o Expertise in k8s o Hands on experience in defining CI/CD pipelines for enterprises e.g. Concord/Looper/etc. o Experience deploying and maintaining high volume APIs o Experience in QA and SRE Nice to Have o Experience with and understanding of best practices in Machine Learning, software engineering, and production deployment of ML services o Experience with Kubeflow, MLFlow and MLOps practices Experience deploying applications in GCP and Azure Thanks & Regards Shikha Singh Sr Technical Recruiter Email: - [email protected] https://convextech.com/ -- Keywords: continuous integration continuous deployment quality analyst artificial intelligence machine learning access management information technology microsoft Arkansas Texas DevOps with Machine Learning DevOps with Machine Learning [email protected] |
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| Fri Jul 26 21:51:00 UTC 2024 |