Job Overview

Adobe is hiring a Machine Learning Engineer in Noida, Uttar Pradesh, to work on large-scale search, discovery, recommendation, content understanding, and generative AI systems. The role sits within Adobe's Search, Discovery, and Content AI organization and focuses on building machine learning capabilities that help users find, understand, and interact with digital content more effectively.

The position combines machine learning engineering, distributed data processing, search technology, generative AI, and real-time systems. You will contribute to production solutions supporting large volumes of content across Adobe products and services. The work spans the complete machine learning lifecycle, from data preparation and model development to deployment, monitoring, optimization, and continuous improvement.

This is an experienced engineering opportunity for professionals who enjoy solving complex problems involving large datasets, intelligent search, recommendations, multimodal AI, and scalable production platforms.

Key Responsibilities

• Develop, evaluate, and improve machine learning models for search, recommendations, ranking, and content understanding.
• Build scalable AI and generative AI solutions that can operate reliably in production environments.
• Work with large datasets and distributed processing systems to support content ingestion, indexing, analytics, and machine learning workflows.
• Contribute to search systems capable of processing and indexing very large volumes of digital assets.
• Improve search relevance and recommendation quality through machine learning, analytics, and experimentation.
• Build and enhance components involved in data preprocessing, model training, evaluation, deployment, and monitoring.
• Apply deep learning approaches to areas such as computer vision, natural language understanding, and multimodal learning.
• Integrate machine learning models into production software while considering performance, scalability, reliability, and operational requirements.
• Work with product and engineering teams to translate customer needs into practical technical solutions.
• Investigate new approaches in machine learning and generative AI and assess their suitability for real-world applications.
• Mentor junior engineers and provide technical guidance to cross-functional collaborators.
• Help improve computational efficiency for systems that need to deliver intelligent results in real time.

Required Skills

Strong Python programming skills are important for machine learning and AI development. Knowledge of Java is useful for building production-grade systems.

Candidates should have strong fundamentals in machine learning, including linear algebra, statistics, optimization, and numerical methods. Practical experience with machine learning frameworks such as TensorFlow or PyTorch is expected.

The role requires experience working with large-scale data, distributed systems, search technologies, and production machine learning platforms. Candidates should be comfortable designing solutions that remain reliable and performant as data volume and user demand increase.

Experience with AWS resources and cloud-based engineering is also required. Familiarity with production software engineering and SaaS environments will help candidates work effectively with the broader platform ecosystem.

Preferred Skills

Experience with generative AI technologies and content-focused applications is valuable. Exposure to systems and models such as Stable Diffusion, DALL·E, or Midjourney can be useful for relevant AI use cases.

Experience with Elasticsearch or Solr and search indexing pipelines is preferred. Candidates with knowledge of real-time recommendation systems, search relevance, computational geometry, 3D modeling, animation pipelines, or multimodal applications may also have an advantage.

Experience with REST web services, RDBMS, and NoSQL databases is beneficial. Publications in relevant peer-reviewed journals or conferences may also strengthen an application.

Education

A Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Data Science, or a related discipline is required. An advanced degree, including a Ph.D. in a relevant field, is preferred.

Experience

The position requires 6 to 9 years of industry experience developing and deploying machine learning systems at scale. Candidates should have demonstrated experience taking ML solutions from development into production and improving their performance and reliability.

Experience should include practical work with large-scale data processing, machine learning models, distributed systems, search technology, cloud resources, and production software. Experience engineering SaaS-based software is also relevant to the role.

Required Technologies

• Python
• Java
• TensorFlow
• PyTorch
• AWS
• Elasticsearch
• REST
• SQS
• Apache Kafka
• Hadoop
• Kubernetes
• Apache Spark
• Machine Learning
• Deep Learning
• Computer Vision
• Natural Language Understanding
• Transformers
• BERT
• GPT
• Generative AI
• Search Indexing
• Recommendation Systems
• RDBMS
• NoSQL
• Distributed Systems

Soft Skills

Strong problem-solving ability is essential because the role involves complex machine learning, search, data, and distributed-system challenges. Candidates should be comfortable exploring uncertain problems, testing ideas, and turning research or experimentation into practical engineering solutions.

Clear communication and collaboration are also important. The position involves working with product teams, engineers, researchers, and other cross-functional groups. Senior-level candidates should be able to explain technical decisions clearly and provide guidance to junior engineers and collaborators.

Benefits of Working in this Role

The role provides an opportunity to work on large-scale AI and machine learning systems used across Adobe's ecosystem. Engineers can gain practical experience with search, recommendation systems, generative AI, multimodal learning, distributed computing, cloud infrastructure, and real-time content processing.

The position also offers exposure to projects with broad user impact and the opportunity to work on challenging engineering problems involving very large datasets and production AI systems.

Work Mode

The job description does not explicitly specify an onsite, hybrid, or remote work arrangement. Candidates should confirm the current work model with Adobe during the hiring process.

Location

This Machine Learning Engineer position is based in Noida, Uttar Pradesh, India.

Who Should Apply

This opportunity is well suited to experienced Machine Learning Engineers, AI Engineers, Applied Machine Learning Engineers, Search Engineers, Recommendation Engineers, and Data Scientists with strong production engineering experience.

Candidates with 6 to 9 years of relevant industry experience and hands-on expertise in Python, machine learning frameworks, large-scale data processing, cloud platforms, search technology, and distributed systems should consider applying.

Professionals who have worked on generative AI, computer vision, natural language understanding, recommendation systems, search indexing, or multimodal AI will find strong alignment with the technical focus of the role.

Career Growth

This role can help experienced engineers deepen their expertise in production AI and large-scale machine learning systems. Working across search, recommendations, generative AI, cloud platforms, and distributed computing can support future progression toward Senior Machine Learning Engineer, Staff Machine Learning Engineer, AI Architect, Search Architect, ML Platform Engineer, or technical leadership positions.

Application Advice

Your resume should clearly show production machine learning projects and the technologies used to build and deploy them. Highlight measurable outcomes such as improvements in search relevance, recommendation quality, model performance, processing efficiency, reliability, or system scalability where available.

Emphasize hands-on experience with Python, TensorFlow, PyTorch, AWS, Kubernetes, Spark, Hadoop, Elasticsearch, Kafka, and other technologies that match the position. If you have developed generative AI, computer vision, natural language, multimodal, or real-time recommendation solutions, describe the engineering problem and your contribution clearly.

Also mention experience with large-scale data, distributed systems, REST services, databases, and SaaS applications. Senior candidates should demonstrate both technical depth and the ability to collaborate across teams and mentor other engineers.