AI/ML Architect

2 weeks ago

India InOrg Global Full time

We are seeking a highly skilled AI/ML Architect with extensive experience in cloud technologies to lead the design and implementation of cutting-edge artificial intelligence and machine learning solutions. The ideal candidate will have a deep understanding of AI/ML algorithms, frameworks, and tools, coupled with a strong background in architecting scalable and efficient systems on cloud platforms. As an AI/ML Architect, you will play a critical role in driving innovation, leveraging cloud services to develop and deploy AI/ML models that address complex business challenges.


Responsibilities:

  1. Architecture and Design: Design and architect end-to-end AI/ML solutions that encompass data ingestion, preprocessing, model training, evaluation, deployment, and monitoring, leveraging cloud-based infrastructure and services.
  2. Algorithm Selection and Development: Assess business requirements and select appropriate AI/ML algorithms, frameworks, and techniques to solve specific problems, ensuring accuracy, scalability, and efficiency
  3. Model Training and Optimization: Lead the development and training of machine learning models using large-scale datasets, employing techniques such as hyperparameter tuning, feature engineering, and ensemble learning.
  4. Cloud Integration: Integrate AI/ML solutions with cloud platforms such as AWS, Azure, or Google Cloud Platform, leveraging cloud-based services for data storage, processing, and compute resources.
  5. Scalability and Performance: Architect scalable and high-performance AI/ML systems capable of handling large volumes of data and processing intensive workloads efficiently in cloud environments.
  6. Deployment and Automation: Implement automated pipelines for model deployment and inference, utilizing CI/CD practices, containerization (e.g., Docker), and orchestration tools (e.g., Kubernetes) for efficient deployment and management.
  7. Monitoring and Optimization: Implement monitoring and logging solutions to track model performance, detect anomalies, and optimize resource utilization in production environments.
  8. Security and Compliance: Ensure the security and compliance of AI/ML solutions, implementing best practices for data privacy, access control, and regulatory requirements in cloud-based deployments.
  9. Collaboration and Communication: Collaborate closely with cross-functional teams including data scientists, software engineers, and business stakeholders to understand requirements, define solution architectures, and communicate technical concepts effectively.


Requirements:

  1. Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field.
  2. 12+ years of experience in software development, data engineering, or AI/ML engineering roles, with a focus on architecting and implementing AI/ML solutions.
  3. Strong proficiency in AI/ML algorithms, frameworks, and libraries (e.g., TensorFlow, PyTorch, scikit-learn) for both supervised and unsupervised learning tasks.
  4. Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, including familiarity with cloud-native services for AI/ML (e.g., AWS SageMaker, Azure Machine Learning, Google AI Platform).
  5. Proficiency in programming languages such as Python, Java, or Scala, with experience in developing and deploying production-grade code for AI/ML applications.
  6. Solid understanding of distributed computing principles, big data technologies, and cloud-based data processing frameworks (e.g., Apache Spark, Hadoop).
  7. Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes) for deploying and managing AI/ML workloads in cloud environments.
  8. Excellent problem-solving skills, with the ability to analyze complex data, identify patterns, and develop innovative AI/ML solutions to address business challenges.
  9. Strong communication and interpersonal skills, with the ability to collaborate effectively with multidisciplinary teams and stakeholders.
  10. Experience with DevOps practices and Agile software development methodologies and familiarity with tools such as Jira, Confluence, or similar for Agile project management.
  11. Willing to work on a startup like environment - fast paced, challenging.


Preferred Qualifications:

  1. Advanced degree (e.g., Master’s) in Computer Science, Artificial Intelligence, Machine Learning, or related field.
  2. Certifications in AI/ML (e.g., AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate) and cloud platforms.
  3. Experience with deep learning techniques and neural network architectures for computer vision, natural language processing, or reinforcement learning.
  4. Knowledge of data engineering principles and practices, including data pipeline development, data warehousing, and ETL processes.
  5. Familiarity with MLOps practices and tools for managing the lifecycle of AI/ML models in production environments.
  6. Experience with streaming data processing technologies (e.g., Apache Kafka, Amazon Kinesis) for real-time AI/ML applications.
  7. Strong understanding of data privacy regulations (e.g., GDPR, HIPAA) and experience implementing compliance controls in AI/ML solutions.
  8. Contributions to open-source AI/ML projects or publications in peer-reviewed journals/conferences.


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