About the Role

As a Machine Learning Engineer at InMobi, you will be instrumental in designing, developing, deploying, and maintaining cutting-edge ML systems that power our product experiences. We're looking for someone with a passion for elegant problem-solving, rapid experimentation, and owning end-to-end machine learning workflows.

You will work closely with data scientists and cross-functional teams to build robust data pipelines, scalable platforms, and production-ready ML services.

Key Responsibilities

- Model Development Deployment

- Design, train, and deploy machine learning models with a strong focus on quick, reliable

- Build APIs and microservices to serve ML models at

- Feature development Engineering

- Design deliver asks on backend features efficiently deliver

- Work closely with the analytics, architects PM to deliver features asks as per

- Identify solutions that can help us improve scalability, minimize bugs and reduce cost

- Understanding of when to escalate questions/issues that arise during development

- Able to efficiently diagnose bugs and issues

- Familiar with various design and architectural patterns

- Pipeline Infrastructure

- Develop and maintain data ingestion, preprocessing, and model training

- Deploy scalable data and model solutions that improve efficiency across ML

- Collaboration Integration

- Define and execute end-to-end ML solutions from ideation to

- Monitoring Research

- Monitor model performance in production, using statistical methods to ensure

- Ownership Delivery

- Lead or contribute to POCs and full-scale ML feature

- Manage project deadlines and deliverables in an agile

Basic Qualifications

- Bachelors degree with 4 years OR Masters degree with 3 years in Computer Science, Machine Learning, Data Science, or related

- Proven experience in developing and deploying ML models in

- Strong proficiency in Python and ML libraries like TensorFlow, PyTorch, or scikit-learn, spark, java distributed





- Understanding of statistical methods and hypothesis

- Comfortable working with structured and unstructured

- Experience working in collaborative, cross-functional

- Loves to code and learn new concepts, technologies and frameworks

Preferred Qualifications

- Demonstrated ability to rapidly validate hypotheses through

- Experience in building recommendation systems or similar ML

- Exposure to advertising, ranking, or personalization systems is a significant

- Familiarity with SQL, data warehousing, and distributed data

- Prior research experience or involvement in a data science-focused

- Strong mathematical foundation, particularly in statistics and linear

- Excellent verbal and written communication

- Hands on experience in Databricks is a

- Experience in the ad tech industry a plus

Nice to have skills

- Experience of online advertising domain

- Experience of working on massively large scale data systems in production environments

- Experience in leveraging user data for behavioral targeting and ad-relevance

- Experience of Big Data analytics domain

- Experience of building products that are powered by data and insights

- Experience on hosting and deploying application on public cloud like Msft Azure, GCP,

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Role: Blockchain Quality Assurance Engineer,

Industry Type: Advertising & Marketing,

Department: Engineering - Software & QA,

Employment Type: Full Time, Permanent

Role Category: Quality Assurance and Testing

Education

UG: B.Tech / B.E. in Any Specialization, Any Graduate

PG: Any Postgraduate

Key Skills ad techadvertisingagileaialgorithmsanalyticsapisarchitectural patternsarchitectureaudience targetingazurebig datacloudcommunication and interpersonal skillsconcurrencydata ingestiondata pipelinesdata science

📌 Machine Learning Engineer II - Backend (Bengaluru)
🏢 InMobi
📍 Bengaluru