Machine Learning Engineer

Job Description:

• Is this a remote position? If not, what US Bank locations can a resource work and how many days a week will they be required to work onsite?

1. remote position: hybrid or remote

2. US Bank locations: PD-CA-5232 - Cupertino De Anza / PD-CA-SF - San Francisco Office

3. how many days a week: Two days

• Can you please provide a summary of the project/initiatives which describes what's being done?

1. We will develop an AI/ML Model Inferencing Pipeline that would automate the extraction of all data elements from the Document or from Source Streaming Data, this will leverage the elastic nature of cloud for cost optimize for different use cases.

• What are the top 5-10 responsibilities for this position? (Please be detailed as to what the candidate is expected to do or complete on a daily basis)

1. You will design, develop, test, deploy, maintain, and enhance Machine Learning Pipelines using K8s/AKS based Argo Workflow Orchestration solutions.

2. Participate and contribute to design reviews with platform engineering team to decide the design, technologies, project priorities, deadlines, and deliverables.

3. You will work closely with Data Lake and Data Science team to understand their data structure and machine learning algorithms.

4. Understanding of ETL pipelines, and ingress / egress methodologies and design patterns

5. Implement real time argo workflow pipelines, integrate pipelines with machine learning models, and translate dataand model results into business stakeholders Data Lake

6. Develop distributed Machine Learning Pipeline for training & inferencing using Argo, Spark & AKS

7. Build highly scalable backend REST APIs to collect data from Data Lake and other use-cases / scenarios.

8. Deploy Application in Azure Kubernetes Service using GitLab CICD, Jenkins, Docker, Kubectl, Helm and Mainfest

9. Experience in branching, tagging and maintaining the versions across the different environments in GitLab.

10. Review code developed by other developers and provide a feedback to ensure best practices (e.g., checking code in, accuracy, testability, and efficiency)

11. Debug/track/resolve by analyzing the sources of issues and the impact on application, network, or service operations and quality.

12. Functional, benchmark & performance testing and tuning for the built workflows.

13. Assess, design & optimize the resources capacities (e.g .Memory, GPU etc.) for ML based resource intensive workloads

• What skills/technologies are required (please include the number of years of experience required)?

1. Bachelor's/Master's degree in Computer Science or Data Science

2. 5 to 8 years of experience in software development and with data structures/algorithms

3. 5 to 7 years of experience with programming language Python or JAVA, database languages (e.g., SQL and no-sql)

4. 5 years of experience in developing large-scale infrastructure, distributed systems or networks, experience with compute technologies, storage architecture

5. Strong understanding of microservices architecture and experience with building and deploying RestAPI's using Python, Flask and Django

6. 5 years of experience with Unit and Functional test cases using PyTest, UnitTest and Mocking External Services for functional and non-functional requirements

7. Strong understanding and experience with Kubernetes for availability and scalability of the application in Azure Kubernetes Service

8. Experience in building and deploying applications with Azure, using third-party tools (e.g., Docker, Kubernetes and Terraform)

9. Experience with cloud tools like Azure and Google Cloud Platform

10. Experience with development tools, CI/CD pipelines such as GitLab CI/CD, Artifactory, Cloudbees and Jenkins

• What skills/attributes are preferred (these are a desired, not required)?

1. Python, Kubernets, Argo Workflow, Argo Event, Hive, SQL, no-sql, RestAPI's, Helm, Docker, Jenkins

• What does the interview process look like?

1. How many rounds? 4 rounds

2. Video, phone, or in person? Video

3. How technical will the interviews be? First 1 Technical Skill Check, 2 rounds of technical coding interview, 1 round of system design.

------------------------DO NOT EDIT BELOW THIS LINE, PLEASE INSERT JOB DESCRIPTION ABOVE---------------------------------

Is responsible for developing, implementing and maintaining knowledge-based or artificial intelligence application systems. The individual should ensure that information is converted into a format that is digestible and easy for end users to access the information and utilize it optimally.

ESSENTIAL FUNCTIONS:

? Designs and writes complex code in several languages relevant to our existing product stack, with a focus on automation

? Configures, tunes, maintains and installs applications systems and validates system functionality

? Monitors and fine tunes applications system to achieve optimum performance levels and works with hardware teams to resolve issues with hardware and software

? Develops and maintains department's knowledge database containing enterprise issues and possible resolutions.

? Develops models of task problem domain for which a system will be designed or built.

? Uses models, hypotheses, and cognitive analysis techniques to elicit real problem-solving knowledge from the experts

? Mediates between the expert and knowledge base; encodes for the knowledge base

? Acts as subject matter expert for difficult or complex application problems requiring interpretation of AI tools and principles

? Researches and prepares reports and studies on various aspects of knowledge acquisition, modeling, management, and presentation

? Develops and maintains processes, procedures, models, and templates for collecting and organizing knowledge into specialized knowledge representation programs

? Acts as vendor liaison for products and services to support development tools

? Maintains the definition, documentation, training, testing, and activation of Disaster Recovery/Business Continuity Planning to meet compliance standards

? Maintains a comprehensive operating system hardware and software configuration database/library of all supporting documentation to ensure data integrity

? Acts to improve the overall reliability of systems and to increase efficiency

? Works collaboratively with cross functional teams, using Agile / DevOps principles to bring products to life, achieve business objectives and serve customer needs

Required Skills : Strong Kubernetes experience - Strong Python or Java experience - Experience with ETL Pipelines and Machine Learning Pipelines - Aware of Machine Learning platform infrastructure and tools - Cloud experience - Data Engineering background preferred, would be good to have in this role.Background Check :YesNotes :Selling points for candidate :Project Verification Info :"The information provided below is for Apex Systems AV use only and is not to be distributed publicly, or to any third party. Any distribution of the below information will result in corrective action from Apex Systems Vendor Management. MSA: Restricted Client Letter: Will Provide"Candidate must be your W2 Employee :YesExclusive to Apex :NoFace to face interview required :NoCandidate must be local :NoCandidate must be authorized to work without sponsorship ::NoInterview times set : :NoType of project :Development/EngineeringMaster Job Title :AI: Machine Learning Dev/EngBranch Code :Portland #J-18808-Ljbffr

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