Python Developer (W2)

Overview

Hybrid
Depends on Experience
Full Time

Skills

Artificial Intelligence
Bash
Generative Artificial Intelligence (AI)
DevOps
Google Cloud
Google Cloud Platform
Jenkins
Kubernetes
Machine Learning (ML)
Python
Machine Learning Operations (ML Ops)

Job Details

We, Miracle Software Systems, are looking for a Python Developer- Google Cloud Platform on W2/Full-Time.

Role: Python Developer (8+ Years)
Location: Dearborn, Michigan
Duration: 12+Months
 
Position Description:
At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow's transportation.
 
The Global Data Insight & Analytics organization is seeking a Software Engineer to lead and advance our internal Data Science and AI/ML platform strategy. In this role, you will be part of a dynamic, cross-functional team, collaborating closely and consistently with other engineers, business partners, product managers, and designers. You will be involved in frequent and iterative releases. Your focus will be on software engineering, specifically in developing machine learning and generative AI applications, as well as creating reusable AI/ML components.
 
Position Responsibilities:
Work closely with Tech Anchor, Product Manager and Product Owner to deliver MLOPs platform and Gen AI solution in Google Cloud Platform using Python and other tools for the data scientists and business across the company
Work with software and ML engineers/Data Scientist to tackle challenging AIOps and Gen AI problems
Maintain and mange current CI/CD ecosystem and tools
Find ways to automate and continually improve current CI/CD processes and release processes
Examine, inspect codes / scripts and resolve issues
Help innovate standardize machine learning development practices
Experiment, innovate and share knowledge with the team
Lead by example in use of Paired Programming for cross training/upskilling, problem solving, and speed to delivery
Leverage latest ML/Gen AI / Google Cloud Platform/AIOPs/Kubernetes technologies
 
Skills Required:
A Bachelor's degree in Computer Science / Computer Engineering or similar technical discipline
8+ years of work experience as a backend software engineer in Python with exceptional software engineering knowledge
2+ years of experience with Cloud Engineering / Services
Experience in MLOPs and Gen AI LLM, Development experience with building RAG and Multi Agent Application
Experience with ML workflow orchestration tools: Airflow, Kubeflow etc.
Advanced working knowledge of object-oriented/object function programming languages: Python, C/C++
Experience in DevOps: Jenkins/Tekton etc.
Experience with cloud services, preferably Google Cloud Platform Services like Vertex AI, Cloud Function, BigQuery etc.
Experience in container management solution: Kubernetes, Docker
Experience in scripting language: Bash, PowerShell etc.
Experience with Infrastructure as code: Terraform etc.
 
Skills Preferred:
Master focused in Computer Science / Machine Learning or related field
Experience working with Google Cloud platform(Google Cloud Platform) specifically Google Kubernetes engine, Terraform, and infrastructure
Experience in programming concepts such as Paired Programming, Test Driven Development, etc.
Knowledge of coding and software craftsmanship practices
Must be a quick learner and open to learning new technology
Experience applying agile practices to solution delivery
Must be team-oriented and have excellent oral and written communication skills
Must be a self-starter to understand existing bottlenecks and come up with innovative solutions
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.