DE-Azure ML And AI Engineer

6 - 8 years

15 - 16 Lacs

bengaluru

Posted:1 day ago| Platform:

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Skills Required

azure databricks algorithms python azure data lake training data pipeline azure data factory machine learning data engineering azure devops azure cloud docker git devops design model development cloud computing programming communication skills ml

Work Mode

Work from Office

Job Type

Full Time

Job Description

Develop and deploy machine learning models on Azure cloud platform using Python programming language and Azure ML services.
Design and implement scalable and efficient data pipelines for model training and inference.
Collaborate with data scientists and business stakeholders to understand requirements and translate them into technical solutions.
Implement best practices for ML development, including version control, testing, and documentation.
Develop and maintain APIs on Azure cloud platform for model deployment and integration with applications.
Monitor and optimize model performance, ensuring scalability, reliability, and security.
Participate in code reviews, troubleshooting, and optimization to improve performance and maintainability.
Stay updated with industry trends and best practices in machine learning, cloud computing, and API development.
Mentor junior team members, sharing expertise and guiding them in technical challenges.
Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to deliver end-to-end solutions.
Conduct regular evaluations and assessments of ML models and APIs, identifying areas for improvement and optimization.
Lead and contribute to innovation initiatives, exploring new technologies and approaches to enhance our ML and cloud capabilities.

Soft Skills

Bachelors degree in computer science, data science, or related field.
6-8 years of experience in machine learning, data engineering, and cloud computing, with a strong focus on Azure services.
Proficiency in Python programming language for ML model development and deployment.
Experience with Azure ML services, Azure data services (e.g., Azure Data Lake, Azure SQL Database), and Azure cloud infrastructure.
Strong understanding of machine learning concepts, algorithms, and techniques, including supervised and unsupervised learning, deep learning, and natural language processing.
Expertise in designing and implementing data pipelines for ML model training and inference, using tools like Azure Databricks, Azure Data Factory, and Azure Synapse Analytics.
Familiarity with cloud-native technologies, containerization (e.g., Docker, Kubernetes), and DevOps practices for ML model deployment and automation.
Experience with version control systems (e.g., Git/GitHub), CI/CD pipelines, and software engineering best practices for ML projects.
Strong analytical and problem-solving skills, with the ability to analyze complex data sets, identify patterns, and derive meaningful insights.
Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
Proactive mindset, self-driven, and eager to learn new technologies and methodologies in the ML and cloud computing space.
Ability to work in a fast-paced environment, manage multiple priorities, and deliver high-quality results under tight deadlines.

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