Ml architect Job at Codebase Inc, Chicago, IL

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  • Codebase Inc
  • Chicago, IL

Job Description

Role: ML Architect

Location: Chicago,IL(Onsite)

Job Type: C2C or W2

Position : ML Architect

Location : Chicago , IL

Duration : 1 Year

The ML Architect designs and deploys scalable machine learning systems, ensuring models are production-ready, secure, and efficient. This role focuses on building ML pipelines, deploying models, and maintaining best practices for MLOps.

Qualifications:

  • Bachelor's or Master’s Degree in Computer Science, Data Engineering, Machine Learning, or related field.
  • Preferred: Certification in cloud platforms (Azure, AWS, GCP) or MLOps.

Experience:

  • 7-9+ years of experience in machine learning, software engineering, or data engineering.
  • 3-4 years of experience deploying ML models in production environments.
  • Experience with cloud platforms, MLOps practices, and large-scale systems in the QSR or retail industry is highly beneficial.

Key Skills:

System Design & Architecture:

  • Experience designing and deploying machine learning systems that scale across thousands of locations.
  • Building real-time recommendation engines for digital ordering platforms.

Model Deployment & MLOps:

  • Proficiency in MLOps practices for continuous integration, delivery, and deployment (CI/CD).
  • Familiarity with cloud-based ML services (Azure ML, SageMaker, GCP Vertex AI).
  • Experience in containerization (Docker) and orchestration (Kubernetes).
  • Knowledge of serverless computing and cloud-native services.

Inventory & Supply Chain Optimization:

  • Building ML solutions for supply chain forecasting, inventory optimization, and waste reduction.

Fraud Detection & Risk Management:

  • Experience in implementing fraud detection systems for payment processing and loyalty programs.

Recommendation Systems:

  • Developing personalized upsell and cross-sell recommendations for digital ordering systems.

Performance Optimization:

  • Ability to optimize model performance and latency for real-time applications.
  • Experience with distributed computing frameworks (Spark, Dask).

Security & Compliance:

  • Ensuring deployed models comply with data privacy regulations (e.g., GDPR, CCPA) and security best practices.
  • Collaboration & Documentation:
  • Ability to collaborate with data scientists, engineers, and DevOps teams.
  • Strong documentation skills for model architecture and deployment processes.

  • Thanks & Regards

Naveen ReddyTalent Acquisition Specialist

| [email protected]

Job Tags

Contract work,

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