Senior AI Engineer

Career Area:

Job Description:

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, youre joining a global team who cares not just about the work we do but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We dont just talk about progress and innovation here we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.

Role Definition

The AI Engineer will perform analytical tasks and initiatives on large datasets to support data-driven business decisions and development. This role involves leveraging AI technologies like GenAI and Deep Learning to enhance business processes and outcomes.

Responsibilities

• Developing and implementing AI models, including deep learning and neural networks, using AI libraries such as Keras, TensorFlow, and PyTorch.
• Exploring and applying Generative AI (Gen AI) and Large Language Models (LLMs) to business problems.
• Designing and implementing data engineering pipelines to support machine learning workflows.
• Directing the data gathering, data mining, and data processing processes in large volumes; creating appropriate data models.
• Conducting research on data model optimisation and algorithms to improve effectiveness and accuracy in data analyses.
• Deploying machine learning models into production environments and ensuring their scalability and reliability.
• Performing hands-on coding and development to build and optimise AI solutions.
• Staying updated with the latest advancements in AI technologies and incorporating them into existing projects.
• Collaborating with cross-functional teams to identify opportunities for AI-driven innovation and improvement.

Skill Descriptors

Machine Learning : Knowledge of principles, technologies, and algorithms of machine learning; ability to develop, implement, and deliver related systems, products, and services.

• Completes specific tasks and initiatives utilising machine learning technologies, such as search engine optimisation.
• Utilises specific tools and techniques to process descriptive and inferential statistics.
• Applies specific computing languages and tools in machine learning, such as R and Python.
• Explores the use of machine learning in ones own areas to make business improvements.
• Conducts data mining and cleaning initiatives.

Analytical Thinking : Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organisational problems and create alternative solutions that resolve these problems.

• Approaches a situation or problem by defining the problem or issue and determining its significance.
• Makes a systematic comparison of two or more alternative solutions.
• Uses flow charts, Pareto charts, fish diagrams, etc. to disclose meaningful data patterns.
• Identifies the major forces, events, and people impacting and impacted by the situation at hand.
• Uses logic and intuition to make inferences about the meaning of the data and arrive at conclusions.

Programming Languages : Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques, and platforms in order to write and modify programming languages.

• Participates in the implementation and support of specialised programming languages.
• Conducts basic reviews on writing a specific programming language within a specific platform.
• Assists with the design and development of specialised programming languages.
• Follows an organisations standards, policies, and guidelines for structured programming specifications.
• Diagnoses and reports minor or routine programming language problems.

AI and Deep Learning : AI experience with deep learning, neural networks, AI libraries like Keras, TensorFlow, PyTorch, and exposure to Generative AI (Gen AI) and Large Language Models (LLMs).

• Develops and implements deep learning models and neural networks.
• Utilises AI libraries such as Keras, TensorFlow, and PyTorch for model development.
• Explores and applies Generative AI and Large Language Models to solve business problems.
• Conducts research on advanced machine learning techniques to enhance model performance and accuracy.

Preferred Languages and Tools

• Programming Languages : Python, SQL,
• AI Libraries : Keras, TensorFlow, PyTorch
• Data Processing Tools : Apache Spark
• Cloud Platforms : AWS
• Data Visualisation Tools : Power BI
• Version Control : Git/GitHub