| MLOPS Architect (Machine Learning / AI Architect) :: Remote :: Contract at Remote, Remote, USA |
| Email: [email protected] |
| Hi, Hope you are doing great. My name is Devendra Pratap Singh and I am a Lead Talent Acquisition at Amaze Systems Inc.. I am reaching out to you on an exciting job opportunity with one of our clients. If you feel Interested then please share me your updated resume along with submission details. Job Title: MLOPS Architect (Machine Learning / AI Architect) Job Location: Remote Type of Hire: Contract Mandatory required skills: AWS, Python, Airflow, Kedro, or Luigi, Hadoop, Spark, or similar frameworks. Experience with graph databases a plus. JD: Designing Cloud Architecture : As an AWS Cloud Architect, youll be responsible for designing cloud architectures, preferably on AWS, Azure, or multi-cloud environments. Your architecture design should enable seamless scalability, flexibility, and efficient resource utilization for MLOps implementations. Data Pipeline Design : Develop data taxonomy and data pipeline designs to ensure efficient data management, processing, and utilization across the AI/ML platform. These pipelines are critical for ingesting, transforming, and serving data to machine learning models. MLOps Implementation : Collaborate with data scientists, engineers, and DevOps teams to implement MLOps best practices. This involves setting up continuous integration and continuous deployment (CI/CD) pipelines for model training, deployment, and monitoring. Infrastructure as Code (IaC) : Use tools like AWS CloudFormation or Terraform to define and provision infrastructure resources. Infrastructure as Code allows you to manage your cloud resources programmatically, ensuring consistency and reproducibility. Security and Compliance : Ensure that the MLOps architecture adheres to security best practices and compliance requirements. Implement access controls, encryption, and monitoring to protect sensitive data and models. Performance Optimization : Optimize cloud resources for cost-effectiveness and performance. Consider factors like auto-scaling, load balancing, and efficient use of compute resources. Monitoring and Troubleshooting : Set up monitoring and alerting for the MLOps infrastructure. Be prepared to troubleshoot issues related to infrastructure, data pipelines, and model deployments. Collaboration and Communication : Work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders. Effective communication is essential to align technical decisions with business goals. Activities: Strong experience in Python Experience in data product development, analytical models, and model governance Experience with AI workflow management tools such as Airflow, Kedro, or Luigi Exposure statistical modeling, machine learning algorithms, and predictive analytics. Highly structured and organized work planning skills Strong understanding of the AI development lifecycle and Agile practices Proficiency in big data technologies like Hadoop, Spark, or similar frameworks. Experience with graph databases a plus. Extensive Experience in working with cloud computing platforms - AWS Proven track record of delivering data products in environments with strict adherence to security and model governance standards. Devendra Pratap Singh | Talent Acquisition Specialist Amaze Systems Inc USA: 8951 Cypress Waters Blvd, Suite 160, Dallas, TX 75019 Canada: 55 York Street, Suite 401, Toronto, ON M5J 1R7 D: +1 ( 4 69) 424-3431 E: [email protected] | www.amaze-systems.com/ USA | Canada | UK | India Amaze Systems is an Equal Opportunity Employer (EOE), and does not discriminate based on age, gender, religion, disability, marital status, race and also adheres to laws relating to non-discrimination on the basis of national origin and citizenship status. -- Keywords: continuous integration continuous deployment artificial intelligence machine learning access management information technology Texas MLOPS Architect (Machine Learning / AI Architect) :: Remote :: Contract [email protected] |
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| Fri Aug 02 00:06:00 UTC 2024 |