Artificial Intelligence/Machine Learning Architect

3 weeks ago

Anywhere in IndiaMultiple Locations InOrg Global Full time

Job Description :


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 :

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- Monitoring and Optimization: Implement monitoring and logging solutions to track model performance, detect anomalies, and optimize resource utilization in production environments.

- 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.

- 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 :

- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field.

- 12+ years of experience in software development, data engineering, or AI/ML engineering roles, with a focus on architecting and implementing AI/ML solutions.

- Strong proficiency in AI/ML algorithms, frameworks, and libraries (e.g., TensorFlow, PyTorch, scikit-learn) for both supervised and unsupervised learning tasks.

- 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).

Proficiency in programming languages such as Python, Java, or Scala, with experience in developing and deploying production-grade code for AI/ML applications.

- Solid understanding of distributed computing principles, big data technologies, and cloud-based data processing frameworks (e.g., Apache Spark, Hadoop).

- Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes) for deploying and managing AI/ML workloads in cloud environments.

- Excellent problem-solving skills, with the ability to analyze complex data, identify patterns, and develop innovative AI/ML solutions to address business challenges.

- Strong communication and interpersonal skills, with the ability to collaborate effectively with multidisciplinary teams and stakeholders.

- Experience with DevOps practices and Agile software development methodologies and familiarity with tools such as Jira, Confluence, or similar for Agile project management.

- Willing to work on a startup like environment fast paced, challenging.

Preferred Qualifications :

- Advanced degree (e.g., Master's) in Computer Science, Artificial Intelligence, Machine Learning, or related field.

- Certifications in AI/ML (e. g., AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate) and cloud platforms.

- Experience with deep learning techniques and neural network architectures for computer vision, natural language processing, or reinforcement learning.

- Knowledge of data engineering principles and practices, including data pipeline development, data warehousing, and ETL processes.

- Familiarity with MLOps practices and tools for managing the lifecycle of AI/ML models in production environments.

- Experience with streaming data processing technologies (e.g., Apache Kafka, Amazon Kinesis) for real-time AI/ML applications.

- Strong understanding of data privacy regulations (e.g., GDPR, HIPAA) and experience implementing compliance controls in AI/ML solutions.

- Contributions to open-source AI/ML projects or publications in peer-reviewed journals/conferences.

(ref:hirist.tech)

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