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ML Ops Engineer Job Opening In New Delhi – Now Hiring Aurigo Software Technologies


Job description

Role Brief:
We are seeking a skilled

ML Ops Engineer

to design, implement, and maintain scalable machine learning and large language model (LLM) pipelines in cloud environments, primarily using AWS services.

This role is critical to ensuring the reliability, efficiency, and performance of ML systems in production.
The ideal candidate will have hands-on experience with AWS tools such as SageMaker, Lambda, Bedrock, Batch with Fargate, and infrastructure components like RDS, DynamoDB, and SQS.

You will be responsible for automating CI/CD workflows, managing auto-scaling APIs, and provisioning cloud resources to support high-performance ML workloads, including RAG systems.

Primary Responsibilities:
Strategizing and implementing scalable infrastructure for ML or LLM model pipelines using tools like and cloudservices such as AWS (e.g.,AWS Batch, Fargate,Bedrock)
Manage auto-scaling mechanisms to handle varying workloads and ensure high availability of Rest APIs
Automate CI/CD pipelines and Lambda functions for model testing, deployment, and updates, reducing manual errorsand improving efficiency.
Amazon SageMaker Pipelines for end-to-end ML workflow automation.

Optimize utilizing step-functions
Conduct drift analysis to detect and respond to data drift, concept drift, and label drift.

Implement mitigation strategies such as automated alerts, model retraining triggers, and performance audits.
Set up reproducible workflows for data preparation, model training, and deployment.
Provision and optimize cloud resources (e.g., GPUs, memory) to meet computational demands of large models like those used in RAG systems
Automate retraining workflows to keep models updated as data evolves
Work closely with data scientists, ML engineers, and DevOps teams to integrate models into production environments.
Implement monitoring tools to track model performance and detect issues like drift or degradation in real- time.

Monitoring dashboards with real-time alerts for pipeline failures or performance issues C Implementing ModelObservability frameworks.

Required Skills:
Education Any Engineering (BE/Btech/ME/Mtech)
Min 4 years of experience with AWS services such as Lambda, Bedrock, Batch with Fargate, RDS (PostgreSQL), DynamoDB, SQS, CloudWatch, API Gateway, SageMaker
Should have hands-on experience in drift analysis, including detecting and mitigating data, concept, and label drift in production ML systems
Knowledge of ML frameworks (e.g., PyTorch, TensorFlow) to understand model requirements during deployment
Experience with Rest API Frameworks like Fast APIs, Flask
Familiarity with model observability like Evidently, Nanny ML, Phoenix and monitoring tools (Grafana etc) and retraining tools like MLflow/ Kubeflow / Airflow
AWS Certified Machine Learning – Specialty –

Good to have this certification

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your ML Ops Potential: Insight & Career Growth Guide


Real-time ML Ops Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for ML Ops in New Delhi, India, highlighting market share and opportunities for professionals in ML Ops roles.

17043 Jobs in India
17043
619 Jobs in New Delhi
619
Download Ml Ops Jobs Trends in New Delhi and India

Are You Looking for ML Ops Engineer Job?

Great news! 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: .

The Work Culture

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 Aurigo Software Technologies adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying India laws and regulations

What Is the Average Salary Range for ML Ops Engineer Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in New Delhi. 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.

What Are the Key Qualifications for ML Ops Engineer?

Key qualifications for ML Ops Engineer typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

How Can I Improve My Chances of Getting Hired for ML Ops Engineer?

To improve your chances of getting hired for ML Ops Engineer, consider enhancing your skills. Check your CV/Résumé Score with our free Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.

Interview Tips for ML Ops Engineer Job Success

Aurigo Software Technologies interview tips for ML Ops Engineer

Here are some tips to help you prepare for and ace your ML Ops Engineer job interview:

Before the Interview:

Research: Learn about the Aurigo Software Technologies's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your ML Ops Engineer interview at Aurigo Software Technologies, 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 Aurigo Software Technologies'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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