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Urgent! ML Ops Engineer Job Opening In India, India – Now Hiring Wenger & Watson
Experience - 5 - 10 yrs
Locations - Bangalore, Chennai, Mumbai, Pune, Hyderabad
Key Responsibilities
Design, develop, and deploy machine learning models using AWS SageMaker for various business applications
Implement end-to-end ML pipelines from data preprocessing to model serving and monitoring
Build and maintain automated model training, validation, and deployment workflows
Optimize model performance, scalability, and cost-effectiveness in production environments
Create interactive ML applications and demos using Gradio for stakeholder demonstrations and user interfaces
Develop robust Python applications for data processing, feature engineering, and model inference
Build APIs and microservices for model serving and integration with existing systems
Implement model versioning, A/B testing frameworks, and continuous integration/deployment practices
ML infrastructure on AWS, including SageMaker endpoints, batch transform jobs, and processing jobs
Monitor model performance, data drift, and system health in production environments
Collaborate with DevOps teams to ensure reliable and scalable ML operations
Implement security best practices for ML systems and data handling
Technical Skills
Expert-level proficiency in Python programming with strong software development practices
Extensive hands-on experience with AWS SageMaker, including training jobs, endpoints, and pipelines
Proven experience with Gradio for building ML application interfaces
Strong background in machine learning algorithms, statistical modeling, and deep learning frameworks (PyTorch, TensorFlow, scikit-learn)
Experience with MLOps practices, model versioning, and deployment strategies
Deep understanding of AWS ecosystem (EC2, S3, Lambda, IAM, CloudFormation)
Experience with containerization technologies (Docker, Kubernetes)
Knowledge of data engineering tools and workflows (Apache Spark, Airflow, or similar)
Familiarity with infrastructure as code and CI/CD pipelines
Strong experience with version control systems (Git), code review processes, and agile development
Excellent problem-solving skills and ability to debug complex distributed systems
Experience with data visualization tools and techniques
Strong communication skills for presenting technical concepts to diverse audiences
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Unlock Your ML Ops Potential: Insight & Career Growth Guide
Real-time ML Ops Jobs Trends in India, India (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for ML Ops in India, India using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 18913 jobs in India and 1330 jobs in India. This comprehensive analysis highlights market share and opportunities for professionals in ML Ops roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Wenger & Watson is currently hiring and seeking a ML Ops Engineer to join their team. Feel free to download the job details.
Wait no longer! Are you also interested in exploring similar jobs? Search now: ML Ops Engineer Jobs India.
An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Wenger & Watson adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a ML Ops Engineer Jobs India varies, but the pay scale is rated "Standard" in India. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for ML Ops Engineer typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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Here are some tips to help you prepare for and ace your job interview:
Before the Interview:To prepare for your ML Ops Engineer interview at Wenger & Watson, research the company, understand the job requirements, and practice common interview questions.
Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Wenger & Watson's products or services and be prepared to discuss how you can contribute to their success.
By following these tips, you can increase your chances of making a positive impression and landing the job!
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