Associate Architect - Machine Learning (Azure)

Reposted 23 Days Ago
Be an Early Applicant
3 Locations
In-Office
Mid level
Artificial Intelligence • Big Data • Machine Learning
The Role
The Associate Architect will lead the development and deployment of machine learning solutions on Azure, manage the ML lifecycle, and optimize existing models while providing technical leadership to project teams.
Summary Generated by Built In

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Role : Associate Architect - Machine Learning (Azure)

Experience : 6- 14 Years

Location: Bangalore

Must have skills:

  • Architect, develop, and deploy traditional machine learning solutions at scale.

  • Lead end-to-end ML lifecycle including data preparation, feature engineering, model development, validation, deployment, and monitoring.

  • Evaluate and optimize existing models using traditional ML techniques.

  • Proven expertise in traditional ML algorithms (regression, decision trees, SVM, ensemble models, clustering, etc.)

  • Strong coding skills in Python with experience in ML libraries such as scikit-learn, XGBoost, LightGBM, etc.

  • Solid grasp of data preprocessing, feature selection, and statistical modeling.

  • Deep understanding of ML pipeline orchestration and model lifecycle management.

  • Ensure adherence to MLOps best practices and drive implementation on Azure cloud.

  • Experience in Azure cloud services including Azure Machine Learning, Azure Data Factory, Blob Storage, and Azure DevOps.

  • Leveraged Azure Cognitive Search and Azure OpenAI Service to build scalable and efficient knowledge retrieval systems, enabling real-time semantic search and contextual answer generation.

  • Ability to design and review ML architecture and system integration strategies.

  • Conducted proof-of-concept projects utilizing Azure’s AI ecosystem to explore agentic AI capabilities, including autonomous decision-making and task delegation.

  • Designed and implemented RAG pipelines on Microsoft Azure, integrating large language models (LLMs) with domain-specific knowledge bases to enhance AI-driven information retrieval and response accuracy.

  • Collaborate with data scientists, data engineers, and product stakeholders to convert business requirements into scalable ML models.

  • Provide technical leadership, mentorship, and architecture-level guidance to project teams.

  • Excellent problem-solving, communication, and stakeholder management skills.

Good to have skills:

  • Certifications in Azure AI Engineer or Azure Solutions Architect.

  • Ability to collaborate with cross-functional teams such as Developers, Project Managers, and other stakeholders to understand their requirements and implement solutions.

    If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

    Skills Required

    • Experience in developing and deploying machine learning solutions at scale
    • Strong coding skills in Python
    • Hands-on experience with ML libraries like scikit-learn, XGBoost, LightGBM
    • Expertise in Azure cloud services including Azure Machine Learning, Azure Data Factory
    • Ability to design ML architecture and system integration strategies
    • Excellent problem-solving and communication skills
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    The Company
    HQ: Marlborough, MA
    3,494 Employees
    Year Founded: 2013

    What We Do

    Quantiphi is an award-winning AI-first digital engineering company driven by the desire to solve transformational problems at the heart of business. Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed.

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