
Only 24h Left: Quality Engineer
3 days ago
We are seeking a highly skilledAI/ML Architectwith a strong foundation inData Engineeringand a proven ability to applyDesign Thinkingin solving complex business challenges. The ideal candidate will play a key role in shaping end-to-end AI/ML solutions from data architecture to model deployment while ensuring the design remains user-centric, scalable, and aligned with business objectives.
Key Responsibilities:
- Lead the architecture and design of AI/ML solutions across multiple business domains.
- Collaborate with stakeholders to identify use cases and translate them into scalable, production-ready ML architectures.
- Leverage design thinking methodologies to drive innovative and user-centric solution design.
- Architect data pipelines and feature engineering processes for structured and unstructured data.
- Oversee the full ML lifecycle including data preprocessing, model training, evaluation, deployment, and monitoring.
- Ensure best practices in MLOps, including CI/CD for ML, model governance, and retraining strategies.
- Collaborate with data scientists, engineers, and product teams to align architecture with business goals.
- Mentor and guide engineering and data science teams on solution design, performance optimization, and system integration.
Job Overview:
We are seeking a highly skilledAI/ML Architectwith a strong foundation inData Engineeringand a proven ability to applyDesign Thinkingin solving complex business challenges. The ideal candidate will play a key role in shaping end-to-end AI/ML solutions from data architecture to model deployment while ensuring the design remains user-centric, scalable, and aligned with business objectives.
Key Responsibilities:
- Lead the architecture and design of AI/ML solutions across multiple business domains.
- Collaborate with stakeholders to identify use cases and translate them into scalable, production-ready ML architectures.
- Leverage design thinking methodologies to drive innovative and user-centric solution design.
- Architect data pipelines and feature engineering processes for structured and unstructured data.
- Oversee the full ML lifecycle including data preprocessing, model training, evaluation, deployment, and monitoring.
- Ensure best practices in MLOps, including CI/CD for ML, model governance, and retraining strategies.
- Collaborate with data scientists, engineers, and product teams to align architecture with business goals.
- Mentor and guide engineering and data science teams on solution design, performance optimization, and system integration.
Role:Data Science & Machine Learning - Other
Industry Type:IT Services & Consulting
Department:Data Science & Analytics
Employment Type:Full Time, Permanent
Role Category:Data Science & Machine Learning
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