About the Company

Adobe is a company dedicated to transforming the world through digital experiences. They provide individuals and organizations, from emerging artists to global brands, with the tools necessary to create and deliver outstanding digital content. Adobe’s mission is to empower people to produce beautiful and powerful images, videos, and applications, and to revolutionize how businesses engage with their customers across all digital platforms. The company is committed to hiring top talent and fostering an exceptional employee experience, emphasizing respect and equal opportunity for all. Adobe believes that innovative ideas can originate from anywhere within the organization, and they encourage employees to contribute their next groundbreaking concepts.

Job Description

Adobe is seeking an AI Engineer to join their team in Bangalore, India. This role involves building and evangelizing customer-facing AI platforms, designing and implementing machine learning pipelines, and specializing in Large Language Model (LLM) serving and GPU architecture. The engineer will be responsible for fine-tuning and optimizing models, understanding various LLM models and their use cases, and demonstrating proficiency in DevOps and LLMOps. Strong communication and an ability to articulate complex AI/ML concepts to both technical and business audiences are essential. The role also requires a commitment to continuous innovation and adaptive learning, staying abreast of emerging AI research and applying new concepts to production systems. Adobe is an equal opportunity employer committed to accessibility and inclusivity.

Responsibilities

• Build scalable, customer-facing AI platforms.
• Evangelize AI platforms to customers and internal stakeholders.
• Ensure the scalability, reliability, and performance of AI platforms.
• Design and implement machine learning (ML) pipelines for experiment management, model management, feature management, and model retraining.
• Implement A/B testing of ML models.
• Design APIs for large-scale model inferencing.
• Serve as a Subject Matter Expert (SME) in Large Language Model (LLM) serving paradigms.
• Possess deep knowledge of GPU architectures and expertise in distributed training and serving of large language models.
• Proficiently use model and data parallel training techniques with frameworks like DeepSpeed and service frameworks like vLLM.
• Demonstrate proven expertise in model fine-tuning and optimization techniques.
• Achieve improved latencies and accuracies in model results.
• Reduce training and resource requirements for fine-tuning LLM and LVM models.
• Exhibit extensive knowledge of different LLM models and provide insights on their applicability based on specific use cases.
• Deliver end-to-end solutions from engineering to production for customer use cases.
• Showcase proven expertise in DevOps and LLMOps practices, including Kubernetes, Docker, and container orchestration.
• Demonstrate a deep understanding of LLM orchestration frameworks such as Flowise, Langflow, and Langgraph.
• Clearly explain complex AI/ML topics and design choices to both technical and business audiences.
• Present AI strategies and results to senior executives, emphasizing their impact.
• Lead cross-functional discussions to resolve issues and achieve engineering consensus.
• Persuade stakeholders and secure support for proposed solution approaches.
• Proactively track emerging AI research, frameworks, and industry design patterns.
• Validate new concepts through rapid experimentation and iterative ‘fail-fast’ testing.
• Translate cutting-edge AI developments into practical improvements for production systems.
• Demonstrate a self-driven commitment to learning and adopting evolving AI technologies.

Qualifications

• Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI.
• Deep knowledge of GPU architectures.
• Expertise in distributed training and serving of large language models.
• Proficient in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM.
• Proven expertise in model fine-tuning and optimization techniques.
• Extensive knowledge of different LLM models.
• Proven experience in delivering end-to-end solutions from engineering to production for specific customer use cases.
• Proven expertise in DevOps and LLMOps practices.
• Knowledgeable in Kubernetes, Docker, and container orchestration.
• Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph.
• Ability to explain complex AI/ML topics and design choices to technical and business audiences.
• Experience in presenting AI strategies and results to senior executives, highlighting impact.
• Ability to lead cross-functional discussions to clarify issues and achieve engineering consensus.
• Ability to persuade stakeholders and secure support on solution approaches.
• Proactively tracks emerging AI research, frameworks, and industry design patterns.
• Validates new concepts through quick experimentation and iterative ‘fail-fast’ testing.
• Translates cutting-edge developments into practical improvements for production systems.
• Demonstrates a self-driven commitment to learning and adopting evolving AI technologies.

Skills

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Other Information

Adobe is committed to being an Equal Employment Opportunity employer and does not discriminate on various protected characteristics. They also strive to make their website accessible and provide accommodations for individuals with disabilities.

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