Generative AI/Machine Learning Engineer and Data Scientist

Key Skills

Aartificial intelligence, Algorithms, AWS, Azure, B2B, BERT, Databricks, DevOps, Docker, Framework, Generative AI, GPT, Machine learning techniques, Python Programming, PyTorch, SQL, TensorFlow

Job Description

The Opportunity

We are seeking a highly skilled Generative AI Engineer and Data Scientist to join our AI/ML/DS team. The ideal candidate will have extensive experience with traditional machine learning techniques, as well as recent work experience with Large Language Models, prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), and related technologies. This role requires a deep understanding of marketing performance metrics and the ability to integrate the latest advancements in Generative AI into our marketing products and practices, both internal and customer-facing. The successful candidate will also be skilled at adapting Generative AI models for various data science problems.

What you'll Do

• Develop, fine-tune, and deploy large language models for various applications.
• Manipulate and build models (traditional ML and generative AI) to extract insights from large data sets.
• Design and implement prompt engineering strategies to optimize model performance.
• Utilize Retrieval-Augmented Generation (RAG) and related techniques to enhance model output.
• Integrate generative AI innovations into marketing products to improve performance and engagement.
• Analyze and interpret marketing performance metrics to inform AI model adjustments.
• Collaborate with cross-functional teams to identify and address AI-related challenges.
• Stay updated with the latest trends and advancements in Generative AI and machine learning.
• Adapt generative AI models for diverse machine learning tasks and applications.
• Demonstrate the latest innovations in generative AI to stakeholders.

What you need to succeed

• Advanced degree in Computer Science, Data Science, Machine Learning, or a related field.
• 6+ years of experience in machine learning and data science, with at least 2 years of experience working with Generative AI models.
• Proven experience with Large Language Models (e.g. GPT, BERT) and prompt engineering.
• Proficiency in Python, SQL, and ML frameworks like PyTorch and TensorFlow.
• Ability to quickly generate working code with a Generative AI coding copilot.
• Expertise in fine-tuning and deploying AI models in production environments.
• Strong knowledge of Retrieval-Augmented Generation (RAG) and related techniques.
• Familiarity with marketing performance metrics and their application in AI models.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.
• Strong communication skills and the ability to present results to non-technical stakeholders.
• Ability to suggest new projects and make a case for their benefits to our business.

Preferred Skills:

• Experience with cloud platforms (e.g. Azure, AWS, Google Cloud) for model deployment.
• Experience with Databricks.
• Experience with DevOps tools like Git and Docker.
• Familiarity with both B2C and B2B marketing.

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $135,200 -- $250,900 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.

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