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Machine Learning Architect

MindBrain
Multiple Locations
6 - 9 Years

Posted on: 23/07/2025

Job Description

Location : Remote.

Experience : 8+ Years.

Job Type : Contract.

Job Overview :


We are seeking a highly skilled Machine Learning Architect to design and implement cutting-edge AI/ML solutions that drive business innovation and operational efficiency.

The ideal candidate will have deep expertise in Google Cloud Platform, Gurobi, and Google OR-Tools, with a proven ability to build scalable, optimized machine learning models for complex decision-making processes.

Key Responsibilities :


- Design and develop robust machine learning architectures aligned with business objectives.

- Implement optimization models using Gurobi and Google OR to address complex operational problems.

- Leverage Google Cloud AI/ML services (Vertex AI, TensorFlow, AutoML) for scalable model training and deployment.

- Build automated pipelines for data preprocessing, model training, evaluation, and deployment.

- Ensure high-performance computing and efficient resource usage in cloud environments.

- Collaborate with data scientists, ML engineers, and business stakeholders to integrate ML solutions into production.

- Monitor, retrain, and enhance model performance to maintain accuracy and efficiency.

- Stay current with emerging AI/ML trends, tools, and best practices.

Required Qualifications :


- Bachelors or Masters degree in Computer Science, AI, Data Science, or a related field.

- 5+ years of experience in machine learning solution architecture and deployment.

- Strong hands-on experience with Google Cloud AI/ML services (Vertex AI, AutoML, BigQuery, etc.

- Deep expertise in optimization modeling using Gurobi and Google OR-Tools.

- Proficiency in Python, TensorFlow, PyTorch, and ML libraries/frameworks.

- Solid understanding of big data processing frameworks (e.g., Apache Spark, BigQuery).

- Excellent problem-solving skills with the ability to work across cross-functional teams.

Preferred Qualifications :


- PhD in Machine Learning, Artificial Intelligence, or a related field.

- Experience with Reinforcement Learning and complex optimization algorithms.

- Working knowledge of MLOps, CI/CD pipelines, and Kubernetes for model lifecycle management.

- Familiarity with Google Cloud security best practices and identity/access management.
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