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Only W2, No C2C - 4 Days Onsite at Dearborn, MI.
Skills Required:
Technical Communication, Communications, Google Cloud Platform, TensorFlow, Data Governance, Machine Learning, Python, Artificial Intelligence & Expert Systems, GitHub, Tekton, Docker, Jira, Microservices, Data Architecture, Agile Software Development, SQL, Java, Spark, Cloud Architecture, Apache Kafka, REST APIs 1. Technical Communication – This person will need to describe clearly the ML/AI Ops needs and strategy to colleagues potentially up to executives across a wide cross section of people from very knowledge to not technically knowledgeable in this area. 2. Communications – In addition to the technical communication needed, this person will need to be a great communicator to work with people in other organizations who are stakeholders and we need to work together and not have there be communication gaps 3. Google Cloud Platform – Deep knowledge of how to implement ML / AI Ops in the GCP Platform specifically is required 4. TensorFlow – 5. Data Governance – This role will need to implement an enterprise data governance model and actively promote the concept of data - protection, sharing, reuse, quality, and standards. 6. Machine Learning – We need an ML Ops expert 7. Python – Some of the ML Ops pipeline will likely need to be setup using this code 8. Artificial Intelligence & Expert Systems – The ML Ops pipeline needs to be set up for AI Agentic Solutions in mind as well. 9. GitHub – This is where our code will reside, so this is needed SEE 10 TO 21 IN ADDITION INFORMATION
Skills Preferred:
Telematics, Machine Learning, Data Modeling, Cloud Infrastructure, Data Mining, Database Design, Troubleshooting (Problem Solving), Labor Supervision 1. Telematics – Knowledge of this is nice, as some of our data will be Telematics data 2. Machine Learning – 3. Data Modeling – In order to understand how the data will interact with the ML Operations. 4. Cloud Infrastructure – 5. Data Mining – 6. Database Design – 7. Troubleshooting (Problem Solving) – 8. Labor Supervision – Will need to mentor and advise junior team members to spread ML Ops expertise across the organization
Experience Required:
• Master's degree or foreign equivalent degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field, and 4 years of experience OR equivalent combination of education and experience (6+ years with Bachelor's Degree). • 4 years of professional experience in: o Data engineering, data product development and software product launches o At least three of the following languages: Java, Python, Spark, Scala, SQL • 3 years of cloud data/software engineering experience building scalable, reliable, and cost-effective production batch and streaming data pipelines using: o Data warehouses like Amazon Redshift, Microsoft Azure Synapse Analytics, Google BigQuery. o Workflow orchestration tools like Airflow. o Relational Database Management System like MySQL, PostgreSQL, and SQL Server. o Real-Time data streaming platform like Apache Kafka, GCP Pub/Sub o Microservices architecture to deliver large-scale real-time data processing application. o REST APIs for compute, storage, operations, and security. o DevOps tools such as Tekton, GitHub Actions, Git, GitHub, Terraform, Docker. o Project management tools like Atlassian JIRA. Even better if you have...
Experience Preferred:
• Ph.D. or foreign equivalent degree in Computer Science, Software Engineering, Information System, Data Engineering, or a related field. • 2 years of experience with ML Model Development and/or MLOps. • Committed code to improve open-source data/software engineering projects • Experience architecting cloud infrastructure and handling application migrations/upgrades. • GCP Professional Certifications. • Demonstrated passion to mine raw data and realize its hidden value. • Passion to experiment/implement state of the art data engineering methods/techniques. • Experience working in an implementation team from concept to operations, providing deep technical subject matter expertise for successful deployment. • Experience implementing methods for automation of all parts of the pipeline to minimize labor in development and production. • Analytics skills to profile data, troubleshoot data pipeline/product issues. • Ability to simplify, clearly communicate complex data/software ideas/problems and work with cross-functional teams and all levels of management independently. • Ability to mentor and advise junior team members
Education Required:
Bachelor's Degree
Education Preferred:
Master's Degree
Additional Information :
***HYBRID / 4 days per week in the office*** 10. Tekton – Will likely be needed to work in our DevOps 11. Docker – Our vendor will be using Docker images, so we will need to know how to account for this. 12. Jira – Our projects are managed in Jira, so knowledge of Jira would be nice. 13. Microservices – Microservices architecture to deliver large-scale real-time data processing application. 14. Data Architecture – Optimize existing ML solutions for performance, security, and cost-effectiveness 15. Agile Software Development – Need to be able to work in an Agile environment, related to Jira and Communication skills 16. SQL – There will be SQL in the pipeline, so knowledge is important 17. Java – May be in the pipeline 18. Spark – May be in the pipeline 19. Cloud Architecture – Knowledge to Build scalable and robust ML data pipelines in the cloud to process large volumes of connected vehicle data to support Client
agentic initiatives. 20. Apache Kafka – Knowledge of this for real time data streaming in the pipeline is important 21. REST APIs – REST APIs for compute, storage, operations, and security.
V2Soft is an Equal Opportunity Employer ( EOE). We welcome applicants from all backgrounds, including individuals with disabilities and veterans.
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Sprachkenntnisse
- English
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