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AI Platform Engineer Job Opening In Bengaluru – Now Hiring Asper.ai


Job description

About the Role

We are looking for a highly skilled Lead - Machine Learning Engineer to lead the design, development, and deployment of large-scale ML solutions that power intelligent business applications.

This role bridges data science, engineering, and product — ensuring that ML models move efficiently from prototype to production with scalability, reliability, and performance.

You’ll collaborate with data scientists, software engineers, and product teams to architect and operationalize machine learning systems that deliver measurable business value.

The ideal candidate combines deep technical expertise in machine learning infrastructure with strong leadership and mentorship capabilities.

Key Responsibilities

1.

Machine Learning System Design & Development

  • Lead the end-to-end development of scalable ML systems — from data processing to model training, validation, deployment, and monitoring.

  • Design high-performance pipelines for feature engineering, model serving, and real-time inference.

  • Build reusable frameworks, SDKs, and components to accelerate ML deployment across teams.

2.

MLOps & Automation

  • Establish CI/CD pipelines for ML models, ensuring reproducibility, traceability, and automated rollout.

  • Define best practices for model versioning, model governance, and monitoring (data drift, performance degradation, etc.).

  • Integrate ML systems into production using cloud-native services (AWS, Azure, GCP) and orchestration tools (Kubernetes, Airflow, Kubeflow).

3.

Leadership & Collaboration

  • Lead and mentor a team of ML engineers, fostering a culture of technical excellence and continuous learning.

  • Partner with data scientists to productionize research models, ensuring robustness, scalability, and maintainability.

  • Work with product and engineering teams to align ML solutions with business objectives and delivery timelines.

4.

Performance Optimization & Innovation

  • Optimize training and inference performance using distributed computing, GPU acceleration, and efficient data pipelines.

  • Evaluate new tools, frameworks, and technologies to improve model performance, scalability, and cost-efficiency.

  • Champion best practices in responsible AI — including fairness, transparency, and compliance.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or related field.

  • 6+ years of experience in machine learning or data engineering, including 3+ years in a senior or lead role.

  • Strong proficiency in Python with experience in ML libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and XGBoost.

  • Knowledge of microservices architecture and API design for ML model serving.

  • Expertise in MLOps tools: MLflow, Kubeflow, Airflow, Docker, Kubernetes, and CI/CD systems (Jenkins, GitHub Actions, Argo).

  • Deep understanding of cloud infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML) and data pipelines (Spark, Kafka, Snowflake, BigQuery).

  • Solid experience with model monitoring, observability, and A/B testing frameworks.

  • Strong understanding of software engineering principles — clean code, testing, version control, and documentation.

  • Excellent communication and leadership skills with a proven track record of cross-functional collaboration.

Nice-to-Have

  • Experience with large language models (LLMs), retrieval-augmented generation (RAG), or generative AI pipelines.

  • Exposure to feature stores (Feast, Tecton) and real-time data systems.

  • Understanding of data governance, ethics, and security in AI systems.

  • Full stack development familiarity to collaborate across front-end and back-end integration of ML services.

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your AI Platform Potential: Insight & Career Growth Guide


Real-time AI Platform 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 AI Platform in Bengaluru, India, highlighting market share and opportunities for professionals in AI Platform roles.

134724 Jobs in India
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7026 Jobs in Bengaluru
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Are You Looking for AI Platform Engineer Job?

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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 Asper.ai 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 AI Platform Engineer Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Bengaluru. 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 AI Platform Engineer?

Key qualifications for AI Platform 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.

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Interview Tips for AI Platform Engineer Job Success

Asper.ai interview tips for AI Platform Engineer

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

Before the Interview:

Research: Learn about the Asper.ai'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:

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Final Thought:

To prepare for your AI Platform Engineer interview at Asper.ai, 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 Asper.ai'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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