12,696 Aiml Developer jobs in India

Job Title: Senior Software Development Engineer/Lead ( Machine learning)

About Media.net:

Media.net is a leading online ad-tech company that develops innovative products for advertisers and publishers. Media.net has one of the most comprehensive portfolios of advertising technology in the industry across search, native, display, mobile, local, products and video. Media.net manages high-quality ad supply on over 500,000 websites and its platform and products are licensed by some of the largest publishers, ad networks and other ad tech companies worldwide.

Media.net is one of the largest contextual advertising company worldwide. Media.net has key operation centers across – North America, Europe and Asia. Media.net's US HQ is based in New York, and Global HQ in Dubai.

We are a cutting-edge AdTech company solving the industry's most complex challenges end-to-end — from real-time bidding infrastructure to ad performance optimization. We harness the power of behavioral and contextual data to drive precision and performance at scale.

What You’ll Do

• Design and implement state-of-the-art Generative AI models and predictive machine learning pipelines tailored to AdTech applications.
• Analyze and process large-scale datasets to extract insights and power intelligent decision-making in real-time environments.
• Build and maintain scalable ML systems that integrate deeply into our bidding, targeting, and ad optimization engines.
• Collaborate closely with product, data, and engineering teams to deploy models in a fast-paced, experimentation-heavy environment.
• Own your models end-to-end: from research and prototyping to deployment and performance monitoring.
• Combine deep technical rigor with a broad understanding of system-level impact to make high-quality architectural decisions.

What You Bring

• Proven 6 - 8 years of experience in GenAI (LLMs, transformers, diffusion, etc.) and predictive ML models (XGBoost, deep learning, time series, etc.).
• Strong proficiency in Python, PyTorch or TensorFlow, and experience with data engineering for ML (Spark, Pandas, etc.).
• Expertise in handling large-scale datasets (terabytes+) in distributed computing environments.
• Deep understanding of ML lifecycle, model deployment, and MLOps best practices.
• A startup mindset: bias for action, comfort with ambiguity, and ability to thrive under rapid iteration cycles.
• Bachelor's, Master’s, or Ph.D. in CS, Data Science, or related field.

Nice to Have

• Experience with real-time systems, ad exchanges, DSPs, or programmatic advertising.
• Contributions to open-source ML projects or published research in GenAI or related areas.

Why Join Us

• Work on real-world GenAI and ML challenges that move millions of dollars in ad revenue.
• Collaborate with a tight-knit, elite engineering team solving meaningful problems at scale.
• Enjoy high ownership, fast iterations, and freedom to innovate.

SDE II – Machine Learning

Location: Bangalore

Experience: 3–6 years

About Media.net

Media.net is a global leader in ad tech, powering billions of ad impressions across web and mobile formats. Our proprietary contextual advertising and machine learning technologies serve major global publishers and advertisers.

We focus on building intelligent systems that solve complex optimization and targeting problems at scale. If you thrive in a fast-paced, data-driven environment and are excited to work on products that impact millions of users daily, Media.net is the place for you.

Role Overview

As an SDE II – Machine Learning, you will be a core contributor in designing, building, and scaling ML-driven systems that power our real-time ad platforms. You'll be responsible for full-stack ML development—from data engineering and model development to scalable deployment—working closely with product, data science, and engineering teams.

What You'll Do

· Build and deploy machine learning models for ranking, bid optimization, and click-through rate prediction.

· Design scalable and fault-tolerant data pipelines and services that serve real-time and batch ML workloads.

· Work with large volumes of structured and unstructured data to extract meaningful patterns.

· Collaborate with data scientists to convert prototypes into production-ready systems.

· Build systems to intelligently target ads and content by combining contextual and behavioral signals.

· Use LLM learning to improve ad relevance, page understanding, and user targeting.

· Continuously experiment and optimize models based on user feedback and system performance.

Some Interesting Challenges You'll Solve

· Predicting CTRs and revenue across millions of unique URLs and topics in real-time.

· Solving cold-start problems with sparse data using explore-exploit frameworks.

· Matching contextual and behavioral data for enhanced user targeting.

· Designing real-time bidding systems that optimize for revenue and win rate.

· Leveraging LLMs/NLP to extract intent and context from web content.

Tech Stack You'll Work With

· Languages: Python, Java, Node.js

· ML/Big Data: Apache Spark, Hadoop, TensorFlow/PyTorch, Kafka

· Databases: SQL, MongoDB, Redis, Elasticsearch

· Cloud: GCP or similar

What We're Looking For

· 3–6 years of hands-on experience in software development and ML engineering.

· Strong programming and debugging skills, preferably in Python and Java.

· Experience building and deploying ML models in production environments.

· Solid understanding of ML algorithms (e.g., decision trees, gradient boosting, deep learning).

· Hands-on experience with large-scale data processing tools (e.g., Spark, Hadoop).

· Ability to design low-latency, high-throughput systems.

· Strong problem-solving and analytical skills.

Bonus Points

· Prior experience with ad tech, recommender systems, or real-time bidding.

· Publications or contributions to ML research or open-source projects.

· Experience with NLP, LLMs, or Information Retrieval.

· Exposure to auction theory or game-theoretic modeling.

Why Join Us?

· Work on high-impact problems that power ad delivery at scale.

· Flexible work hours, modern office spaces, and supportive teams.

· Full-stack ownership and end-to-end involvement in projects.

· Culture that values innovation, autonomy, and deep tech.

Job Title: Senior Software Development Engineer/Lead ( Machine learning)

About Media.net:

Media.net is a leading online ad-tech company that develops innovative products for advertisers and publishers. Media.net has one of the most comprehensive portfolios of advertising technology in the industry across search, native, display, mobile, local, products and video. Media.net manages high-quality ad supply on over 500,000 websites and its platform and products are licensed by some of the largest publishers, ad networks and other ad tech companies worldwide.

Media.net is one of the largest contextual advertising company worldwide. Media.net has key operation centers across – North America, Europe and Asia. Media.net's US HQ is based in New York, and Global HQ in Dubai.

We are a cutting-edge AdTech company solving the industry's most complex challenges end-to-end — from real-time bidding infrastructure to ad performance optimization. We harness the power of behavioral and contextual data to drive precision and performance at scale.

What You’ll Do

• Design and implement state-of-the-art Generative AI models and predictive machine learning pipelines tailored to AdTech applications.
• Analyze and process large-scale datasets to extract insights and power intelligent decision-making in real-time environments.
• Build and maintain scalable ML systems that integrate deeply into our bidding, targeting, and ad optimization engines.
• Collaborate closely with product, data, and engineering teams to deploy models in a fast-paced, experimentation-heavy environment.
• Own your models end-to-end: from research and prototyping to deployment and performance monitoring.
• Combine deep technical rigor with a broad understanding of system-level impact to make high-quality architectural decisions.

What You Bring

• Proven 6 - 8 years of experience in GenAI (LLMs, transformers, diffusion, etc.) and predictive ML models (XGBoost, deep learning, time series, etc.).
• Strong proficiency in Python, PyTorch or TensorFlow, and experience with data engineering for ML (Spark, Pandas, etc.).
• Expertise in handling large-scale datasets (terabytes+) in distributed computing environments.
• Deep understanding of ML lifecycle, model deployment, and MLOps best practices.
• A startup mindset: bias for action, comfort with ambiguity, and ability to thrive under rapid iteration cycles.
• Bachelor's, Master’s, or Ph.D. in CS, Data Science, or related field.

Nice to Have

• Experience with real-time systems, ad exchanges, DSPs, or programmatic advertising.
• Contributions to open-source ML projects or published research in GenAI or related areas.

Why Join Us

• Work on real-world GenAI and ML challenges that move millions of dollars in ad revenue.
• Collaborate with a tight-knit, elite engineering team solving meaningful problems at scale.
• Enjoy high ownership, fast iterations, and freedom to innovate.

SDE II – Machine Learning

Location: Bangalore

Experience: 3–6 years

About Media.net

Media.net is a global leader in ad tech, powering billions of ad impressions across web and mobile formats. Our proprietary contextual advertising and machine learning technologies serve major global publishers and advertisers.

We focus on building intelligent systems that solve complex optimization and targeting problems at scale. If you thrive in a fast-paced, data-driven environment and are excited to work on products that impact millions of users daily, Media.net is the place for you.

Role Overview

As an SDE II – Machine Learning, you will be a core contributor in designing, building, and scaling ML-driven systems that power our real-time ad platforms. You'll be responsible for full-stack ML development—from data engineering and model development to scalable deployment—working closely with product, data science, and engineering teams.

What You'll Do

· Build and deploy machine learning models for ranking, bid optimization, and click-through rate prediction.

· Design scalable and fault-tolerant data pipelines and services that serve real-time and batch ML workloads.

· Work with large volumes of structured and unstructured data to extract meaningful patterns.

· Collaborate with data scientists to convert prototypes into production-ready systems.

· Build systems to intelligently target ads and content by combining contextual and behavioral signals.

· Use LLM learning to improve ad relevance, page understanding, and user targeting.

· Continuously experiment and optimize models based on user feedback and system performance.

Some Interesting Challenges You'll Solve

· Predicting CTRs and revenue across millions of unique URLs and topics in real-time.

· Solving cold-start problems with sparse data using explore-exploit frameworks.

· Matching contextual and behavioral data for enhanced user targeting.

· Designing real-time bidding systems that optimize for revenue and win rate.

· Leveraging LLMs/NLP to extract intent and context from web content.

Tech Stack You'll Work With

· Languages: Python, Java, Node.js

· ML/Big Data: Apache Spark, Hadoop, TensorFlow/PyTorch, Kafka

· Databases: SQL, MongoDB, Redis, Elasticsearch

· Cloud: GCP or similar

What We're Looking For

· 3–6 years of hands-on experience in software development and ML engineering.

· Strong programming and debugging skills, preferably in Python and Java.

· Experience building and deploying ML models in production environments.

· Solid understanding of ML algorithms (e.g., decision trees, gradient boosting, deep learning).

· Hands-on experience with large-scale data processing tools (e.g., Spark, Hadoop).

· Ability to design low-latency, high-throughput systems.

· Strong problem-solving and analytical skills.

Bonus Points

· Prior experience with ad tech, recommender systems, or real-time bidding.

· Publications or contributions to ML research or open-source projects.

· Experience with NLP, LLMs, or Information Retrieval.

· Exposure to auction theory or game-theoretic modeling.

Why Join Us?

· Work on high-impact problems that power ad delivery at scale.

· Flexible work hours, modern office spaces, and supportive teams.

· Full-stack ownership and end-to-end involvement in projects.

· Culture that values innovation, autonomy, and deep tech.

Job Title: Senior Software Development Engineer/Lead ( Machine learning)

About Media.net:

Media.net is a leading online ad-tech company that develops innovative products for advertisers and publishers. Media.net has one of the most comprehensive portfolios of advertising technology in the industry across search, native, display, mobile, local, products and video. Media.net manages high-quality ad supply on over 500,000 websites and its platform and products are licensed by some of the largest publishers, ad networks and other ad tech companies worldwide.

Media.net is one of the largest contextual advertising company worldwide. Media.net has key operation centers across – North America, Europe and Asia. Media.net's US HQ is based in New York, and Global HQ in Dubai.

We are a cutting-edge AdTech company solving the industry's most complex challenges end-to-end — from real-time bidding infrastructure to ad performance optimization. We harness the power of behavioral and contextual data to drive precision and performance at scale.

What You’ll Do

• Design and implement state-of-the-art Generative AI models and predictive machine learning pipelines tailored to AdTech applications.
• Analyze and process large-scale datasets to extract insights and power intelligent decision-making in real-time environments.
• Build and maintain scalable ML systems that integrate deeply into our bidding, targeting, and ad optimization engines.
• Collaborate closely with product, data, and engineering teams to deploy models in a fast-paced, experimentation-heavy environment.
• Own your models end-to-end: from research and prototyping to deployment and performance monitoring.
• Combine deep technical rigor with a broad understanding of system-level impact to make high-quality architectural decisions.

What You Bring

• Proven 6 - 8 years of experience in GenAI (LLMs, transformers, diffusion, etc.) and predictive ML models (XGBoost, deep learning, time series, etc.).
• Strong proficiency in Python, PyTorch or TensorFlow, and experience with data engineering for ML (Spark, Pandas, etc.).
• Expertise in handling large-scale datasets (terabytes+) in distributed computing environments.
• Deep understanding of ML lifecycle, model deployment, and MLOps best practices.
• A startup mindset: bias for action, comfort with ambiguity, and ability to thrive under rapid iteration cycles.
• Bachelor's, Master’s, or Ph.D. in CS, Data Science, or related field.

Nice to Have

• Experience with real-time systems, ad exchanges, DSPs, or programmatic advertising.
• Contributions to open-source ML projects or published research in GenAI or related areas.

Why Join Us

• Work on real-world GenAI and ML challenges that move millions of dollars in ad revenue.
• Collaborate with a tight-knit, elite engineering team solving meaningful problems at scale.
• Enjoy high ownership, fast iterations, and freedom to innovate.

SDE II – Machine Learning

Location: Bangalore

Experience: 3–6 years

About Media.net

Media.net is a global leader in ad tech, powering billions of ad impressions across web and mobile formats. Our proprietary contextual advertising and machine learning technologies serve major global publishers and advertisers.

We focus on building intelligent systems that solve complex optimization and targeting problems at scale. If you thrive in a fast-paced, data-driven environment and are excited to work on products that impact millions of users daily, Media.net is the place for you.

Role Overview

As an SDE II – Machine Learning, you will be a core contributor in designing, building, and scaling ML-driven systems that power our real-time ad platforms. You'll be responsible for full-stack ML development—from data engineering and model development to scalable deployment—working closely with product, data science, and engineering teams.

What You'll Do

· Build and deploy machine learning models for ranking, bid optimization, and click-through rate prediction.

· Design scalable and fault-tolerant data pipelines and services that serve real-time and batch ML workloads.

· Work with large volumes of structured and unstructured data to extract meaningful patterns.

· Collaborate with data scientists to convert prototypes into production-ready systems.

· Build systems to intelligently target ads and content by combining contextual and behavioral signals.

· Use LLM learning to improve ad relevance, page understanding, and user targeting.

· Continuously experiment and optimize models based on user feedback and system performance.

Some Interesting Challenges You'll Solve

· Predicting CTRs and revenue across millions of unique URLs and topics in real-time.

· Solving cold-start problems with sparse data using explore-exploit frameworks.

· Matching contextual and behavioral data for enhanced user targeting.

· Designing real-time bidding systems that optimize for revenue and win rate.

· Leveraging LLMs/NLP to extract intent and context from web content.

Tech Stack You'll Work With

· Languages: Python, Java, Node.js

· ML/Big Data: Apache Spark, Hadoop, TensorFlow/PyTorch, Kafka

· Databases: SQL, MongoDB, Redis, Elasticsearch

· Cloud: GCP or similar

What We're Looking For

· 3–6 years of hands-on experience in software development and ML engineering.

· Strong programming and debugging skills, preferably in Python and Java.

· Experience building and deploying ML models in production environments.

· Solid understanding of ML algorithms (e.g., decision trees, gradient boosting, deep learning).

· Hands-on experience with large-scale data processing tools (e.g., Spark, Hadoop).

· Ability to design low-latency, high-throughput systems.

· Strong problem-solving and analytical skills.

Bonus Points

· Prior experience with ad tech, recommender systems, or real-time bidding.

· Publications or contributions to ML research or open-source projects.

· Experience with NLP, LLMs, or Information Retrieval.

· Exposure to auction theory or game-theoretic modeling.

Why Join Us?

· Work on high-impact problems that power ad delivery at scale.

· Flexible work hours, modern office spaces, and supportive teams.

· Full-stack ownership and end-to-end involvement in projects.

· Culture that values innovation, autonomy, and deep tech.