About the Company

Adobe is a global leader dedicated to transforming the world through digital experiences. They provide a comprehensive suite of tools and resources for individuals and organizations, from emerging artists to large enterprises, enabling them to design and deliver exceptional digital content. Adobe is passionate about empowering creativity and innovation, facilitating the creation of stunning images, videos, and applications, and revolutionizing how businesses engage with customers across all digital platforms. The company is committed to attracting top talent and fostering an inclusive work environment where every employee is valued, respected, and has equal opportunities for growth. Adobe believes that groundbreaking ideas can emerge from any level of the organization and actively encourages new perspectives.

Job Description

Adobe is seeking a highly skilled and motivated AI Engineer to join their team in Bangalore, India. This role involves developing and evangelizing customer-facing AI platforms, designing and implementing robust machine learning pipelines, and possessing deep expertise in Large Language Model (LLM) serving and GPU architectures. The successful candidate will be responsible for fine-tuning and optimizing models, understanding various LLM models and their use cases, and applying strong DevOps and LLMOps principles. Excellent communication and articulation skills are essential for explaining complex AI/ML concepts to diverse audiences, and a proactive approach to continuous innovation and adaptive learning is highly valued. Adobe is an equal opportunity employer committed to diversity and inclusion.

Responsibilities

• Build scalable, customer-facing AI platforms.
• Evangelize the AI platform to customers and internal stakeholders.
• Ensure the scalability, reliability, and performance of AI platforms.
• Design machine learning pipelines for experiment management, model management, feature management, and model retraining.
• Implement A/B testing for machine learning models.
• Design APIs for large-scale model inferencing.
• Serve as a subject matter expert in LLM serving paradigms.
• Possess deep knowledge of GPU architectures and distributed training/serving of large language models.
• Be proficient in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM.
• Demonstrate expertise in model fine-tuning and optimization techniques to improve latency and accuracy.
• Reduce training and resource requirements for fine-tuning LLM and LVM models.
• Have extensive knowledge of different LLM models and their applicability to various use cases.
• Deliver end-to-end solutions from engineering to production for specific customer use cases.
• Apply DevOps and LLMOps practices, including Kubernetes, Docker, and container orchestration.
• Utilize LLM orchestration frameworks such as Flowise, Langflow, and Langgraph.
• Explain complex AI/ML topics and design choices to both technical and business audiences.
• Present AI strategies and results to senior executives, highlighting their impact.
• Lead cross-functional discussions to clarify 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 quick 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.
• Proficiency in model and data parallel training using frameworks like DeepSpeed.
• Proficiency in 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 an Equal Employment Opportunity employer and does not discriminate based on various protected characteristics. The company is committed to making its website accessible and provides contact information for accommodation requests.

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