Advanced Micro Devices
Senior Applied Data & AI Engineer
Advanced Micro Devices, Austin, Texas, us, 78716
WHAT YOU DO AT AMD CHANGES EVERYTHING
We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.
THE ROLE:
We are seeking a seasoned
Senior Applied Data & AI Engineer
to design and execute impactful data and AI solutions. This role is ideal for professionals with expertise spanning data engineering, data science, and machine learning, capable of building scalable data systems, developing AI models, and integrating solutions into business workflows. As a full-stack applied data & AI engineer, you will wear multiple hats, working across the entire data lifecycle, from pipeline creation and data preparation to AI model deployment and optimization, ensuring seamless delivery of impactful solutions. This position offers the opportunity to work on complex projects, applying advanced technical expertise to solve challenging problems and deliver measurable results. THE PERSON: This AMD team is looking for a passionate senior-level person who can help lead team initiatives, mentor junior developers, and is an excellent team player. The ideal candidate possesses strong analytical, problem-solving, and consulting skills. KEY RESPONSIBILITIES: Data Engineering and Foundations Design, develop, and optimize scalable ETL pipelines to process large-scale structured and unstructured datasets. Create and manage efficient data architectures that support analytics and machine learning needs. Utilize tools like Snowflake and Databricks to deliver high-performance data solutions. Implement rigorous data validation and governance processes to ensure quality and reliability. AI and Machine Learning Execution Build and deploy machine learning models for a wide array of use cases. Develop deep learning and NLP models using frameworks like TensorFlow or PyTorch for complex challenges. Employ advanced AI methodologies, including transformers, LLMs, and GANs, to address business requirements. Design batch and real-time pipelines to integrate AI-driven predictions into operational systems. Project Delivery Adapt to project requirements by serving as a Data Engineer, Data Scientist, or ML Engineer, leveraging expertise across disciplines. Lead the end-to-end execution of data and AI initiatives, ensuring alignment with project goals, timelines, and quality standards. Continuously optimize workflows to improve performance, scalability, and operational efficiency. Collaboration and Innovation Engage with stakeholders to understand business objectives and translate them into technical solutions. Contribute to cross-functional team discussions, sharing expertise and best practices in data and AI. Stay current with advancements in tools, methodologies, and technologies, applying innovations to improve project outcomes. Team player and self-starter. PREFERRED EXPERIENCE: Experience in data engineering, data science, or machine learning roles. Strong expertise in Python, SQL, and machine learning frameworks like TensorFlow or PyTorch. Proven ability to design and optimize ETL pipelines and work with platforms like
Snowflake
or
Databricks . In-depth knowledge of machine learning algorithms, including clustering, regression, and time series analysis. Hands-on experience in deploying and maintaining machine learning models in production environments. Experience in distributed computing frameworks (PySpark, Hadoop). Experience with advanced AI technologies such as transformers, LLMs, and GANs. Proven track record of building real-time pipelines and integrating AI solutions into business systems. Experience in semiconductor manufacturing and/or high-volume manufacturing. ACADEMIC CREDENTIALS: Bachelor’s, Master’s, and 10+ years of directly relevant experience or PhD and 9+ years of experience in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field.
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Senior Applied Data & AI Engineer
to design and execute impactful data and AI solutions. This role is ideal for professionals with expertise spanning data engineering, data science, and machine learning, capable of building scalable data systems, developing AI models, and integrating solutions into business workflows. As a full-stack applied data & AI engineer, you will wear multiple hats, working across the entire data lifecycle, from pipeline creation and data preparation to AI model deployment and optimization, ensuring seamless delivery of impactful solutions. This position offers the opportunity to work on complex projects, applying advanced technical expertise to solve challenging problems and deliver measurable results. THE PERSON: This AMD team is looking for a passionate senior-level person who can help lead team initiatives, mentor junior developers, and is an excellent team player. The ideal candidate possesses strong analytical, problem-solving, and consulting skills. KEY RESPONSIBILITIES: Data Engineering and Foundations Design, develop, and optimize scalable ETL pipelines to process large-scale structured and unstructured datasets. Create and manage efficient data architectures that support analytics and machine learning needs. Utilize tools like Snowflake and Databricks to deliver high-performance data solutions. Implement rigorous data validation and governance processes to ensure quality and reliability. AI and Machine Learning Execution Build and deploy machine learning models for a wide array of use cases. Develop deep learning and NLP models using frameworks like TensorFlow or PyTorch for complex challenges. Employ advanced AI methodologies, including transformers, LLMs, and GANs, to address business requirements. Design batch and real-time pipelines to integrate AI-driven predictions into operational systems. Project Delivery Adapt to project requirements by serving as a Data Engineer, Data Scientist, or ML Engineer, leveraging expertise across disciplines. Lead the end-to-end execution of data and AI initiatives, ensuring alignment with project goals, timelines, and quality standards. Continuously optimize workflows to improve performance, scalability, and operational efficiency. Collaboration and Innovation Engage with stakeholders to understand business objectives and translate them into technical solutions. Contribute to cross-functional team discussions, sharing expertise and best practices in data and AI. Stay current with advancements in tools, methodologies, and technologies, applying innovations to improve project outcomes. Team player and self-starter. PREFERRED EXPERIENCE: Experience in data engineering, data science, or machine learning roles. Strong expertise in Python, SQL, and machine learning frameworks like TensorFlow or PyTorch. Proven ability to design and optimize ETL pipelines and work with platforms like
Snowflake
or
Databricks . In-depth knowledge of machine learning algorithms, including clustering, regression, and time series analysis. Hands-on experience in deploying and maintaining machine learning models in production environments. Experience in distributed computing frameworks (PySpark, Hadoop). Experience with advanced AI technologies such as transformers, LLMs, and GANs. Proven track record of building real-time pipelines and integrating AI solutions into business systems. Experience in semiconductor manufacturing and/or high-volume manufacturing. ACADEMIC CREDENTIALS: Bachelor’s, Master’s, and 10+ years of directly relevant experience or PhD and 9+ years of experience in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field.
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