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AI/ML Architect

2 months ago

Irving, Texas, United States GM Financial Full time
About GM Financial

GM Financial is a leading player in the auto finance industry, driving innovation and modernization through a startup mindset and a commitment to preserving our small company culture within a public company environment.

We are a data-driven organization, leveraging insights to advance our business objectives and achieve our mission of zero emission, zero collision, zero congestion, and zero friction.

With a global presence in LATAM, Europe, China, U.S., and Canada, we are building cutting-edge platforms and seeking talented individuals to join our high-performing team.

As a Blue-Chip company, we are changing the way we use technology to support our customers, dealers, and business.

About the Role

We are seeking an experienced AI/ML Architect to design and develop advanced artificial intelligence solutions for various applications.

The successful candidate will work closely with cross-functional teams to understand business requirements and translate them into scalable and efficient AI architecture.

Key Responsibilities:

  • Design and develop AI architectures, frameworks, and algorithms that can support large-scale and sophisticated AI solutions using Retrieval augmented generation (RAG), Contextual AI, Prompt Engineering, etc.
  • Evaluate and select appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability.
  • Own the development and implementation of AI models, ensuring consistency to standard processes in machine learning and deep learning.
  • Develop and maintain AI pipelines, incorporating data cleaning, pre-processing, feature engineering, model training, and validation processes.
  • Optimize AI models and systems for performance, scalability, and efficiency.
  • Conduct regular code reviews and provide technical guidance to junior members of the team.
  • Stay up to date with the latest advancements in AI technologies, frameworks, and algorithms, and find opportunities for their application in the organization.
  • Collaborate with infrastructure teams to ensure smooth deployment and monitoring of AI models in production environments.
Requirements

To be successful in this role, you will need:

  • 4-6 years of experience as an Architect with a proven track record of implementing innovative solutions and delivering business value.
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
  • Proven experience (3+ years) working as an AI architect, data scientist, or related role.
  • Strong knowledge of machine learning, deep learning, and natural language processing (NLP) techniques.
  • Proficiency in programming languages such as Python, Java, or C++, and familiarity with popular AI libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).
  • Experience in designing and implementing large-scale AI solutions, including data ingestion, storage, processing, and deployment.
  • Solid understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms.
  • Excellent problem-solving and analytical skills, with the ability to break down complex problems into actionable components.
  • Strong communication and collaboration skills, with the ability to work effectively within cross-functional teams.
  • Ability to stay updated with the latest advancements in AI technologies, frameworks, and platforms.
  • Knowledge of ethical considerations and responsible AI practices is a plus.
What We Offer

We offer a generous benefits package, including:

  • 401K matching
  • Bonding leave for new parents (12 weeks, 100% paid)
  • Tuition assistance
  • Training
  • GM employee auto discount
  • Community service pay
  • Nine company holidays
Our Culture

Our team members define and shape our culture, which is built on innovative ideas, integrity, and a sense of community and belonging.

We thrive in an environment that values collaboration, creativity, and continuous learning.