AI/ML Senior Engineer

Position Summary

The Junior AI/ML Engineer - Generative AI Products is a role supporting Corning s Enterprise Generative AI platform as well as AI/ML initiatives across the company. This position focuses on building, testing, and supporting data science and machine learning solutions, including forecasting models, analytics workflows, and Generative AI use cases, under the guidance of senior data scientists and engineers.

Responsibilities

Support development and validation of machine learning and statistical models for business use cases

Assist in building forecasting and predictive models using established techniques and libraries

Contribute to Generative AI use cases including prompt development, evaluation, and basic experimentation with LLMs

Support Retrieval-Augmented Generation (RAG) workflows including document ingestion, embeddings, and retrieval

Perform data preparation, feature engineering, and exploratory data analysis

Work with structured and unstructured data from enterprise sources and AI platforms

Collaborate with software engineers to integrate models into applications and pipelines

Help document models, assumptions, results, and data pipelines

Monitor model performance and assist with troubleshooting and improvements

Participate in agile ceremonies including sprint planning, stand-ups, and retrospectives

Build scalable AI/ML models for given use cases, including price elasticity and recommendation systems, ensuring applicability/reusability across multiple business units.

Leverage tools such as Databricks and AWS SageMaker to manage data, build models, and deploy solutions.

Collaborate with stakeholders, understanding their needs and translating them into AI/ML solutions.

Continually monitor and evaluate the effectiveness of AI/ML models and forecasting techniques, making necessary adjustments to optimize performance.

Stay abreast of the latest AI/ML trends and technologies, identifying opportunities for innovation and improvement.

Education Experience

Bachelor s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. Typically requires 2-4 years of experience in data science, analytics, or machine learning roles, or equivalent academic and project experience.

Required Skills

Proficiency in Python and familiarity with data science libraries (pandas, NumPy, scikit-learn)

Basic understanding of machine learning algorithms and statistical modeling techniques

Experience working with SQL and relational or NoSQL databases

Exposure to cloud or data platforms such as Databricks or AWS

Familiarity with version control tools such as Git

Ability to clearly communicate data insights and document work

Experience working in agile or Scrum-based teams

Desired Skills

Exposure to Generative AI models or LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic)

Familiarity with time-series forecasting methods (ARIMA, Prophet, or similar)

Basic experience with vector databases or similarity search concepts

Experience using notebook environments such as Jupyter

Interest in enterprise AI platforms, data governance, and scalable solutions