Principal AI/ML Engineer

Key Skills

Aartificial intelligence, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, Deep Learning, DevOps, Effective communication skills, Keras software library, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), PyTorch, TensorFlow

Job Description

Responsibilities 

• As a Principal AI/ML Engineer, you be responsible for defining, training, and deploying AI/ML models to solve complex business and semiconductor-specific problems.

• Act as a technical lead for cross-functional teams driving AI R&D and putting models into production, enabling delivery of AI solutions to meet ADI’s strategic goals.

• Perform data engineering and exploratory data analysis to extract meaningful insights; analyze and select features to optimize model performance.

• Explore and select appropriate tools and models for each problem, including using deep learning, LLMs, Transformers, NLP, and ML models.

• Architect and implement solutions adhering to modern software design principles, ensuring best practices in AI architecture, CI/CD, and MLOps.

• Effectively communicate complex technical findings and developments to a diverse audience, including non-technical stakeholders.

• Conduct research to stay ahead of the latest developments in AI, communicate learnings to the team, and evaluate / recommend new technologies for the platform.

Qualifications

• 10+ years of experience in software engineering or data science, including 5+ years developing AI/ML solutions.  At least 3+ years in a technical leadership role.

• Degree in Computer Science, Electrical Engineering, Mathematics, or a related field.  M.S. or Ph.D. preferred.

• Broad understanding of and experience with ML, deep learning, LLMs, and modern AI trends.  Demonstrated deep expertise in at least one specific AI domain.

• Significant experience leading end-to-end AI / data science efforts, from AI use-case analytics, to selecting appropriate models and technologies, to building and deploying working solutions.

• Expertise with relevant languages and technologies such as Python, C++, Azure or AWS.

• Must have extensive experience with deep learning frameworks such as PyTorch, TensorFlow, Keras, etc.

• Demonstrated experience in managing datasets, extracting features, and visualizing results.

• Experience with data orchestration tools and modern DevOps / MLOps processes (e.g., containerization, Docker, Kubernetes).

• Competency in any of the following is also beneficial: electronics and signal processing, control theory, image processing, industrial automation, robotics or silicon fabrication.

• A confident peer influencer with strong communication skills who quickly establishes credibility and is capable of leading cross-functional technical teams.