AI Engineer: Build & Deploy Production ML Solutions

Howmet Aerospace Inc.; Pittsburgh (Allegheny County); On-site; USD 90,000 - 115,000; Full time

Benefits offered by this job

Comprehensive medical, dental, and视ion

Job summary

Howmet Aerospace Inc. in Pittsburgh, PA, is seeking an Artificial Intelligence Engineer to join the Global Information Systems group at the Corporate Center.

You will develop and deploy AI models and related data pipelines, collaborating with data engineers, application developers and analysts. Responsibilities include model development and training, production deployment, API design, data management, and ongoing optimization, with a focus on speed, accuracy and scalability for enterprise

Qualifications

• Bachelor's degree in a technical field and at least 5 years IT experience.
• 2+ years analytics and/or data science experience.
• Working knowledge of SQL and Python; solid math foundation.
• Authorized to work in the United States; visa sponsorship not available.

Responsibilities

• Develop and train AI models and related data pipelines.
• Deploy AI models into production and design model APIs.
• Collaborate with data engineers, developers and analysts.
• Monitor and optimize model performance for speed and accuracy.
• Stay updated with AI advances and apply relevant techniques.

Skills

Communication skills

Continuous learning

Decision making

Prioritization

Project management

Education

Technical bachelor's degree

Bachelor’s in data science or AI

Tools

SQL and Python

TensorFlow/PyTorch/Scikit-learn

Pandas/NumPy/Matplotlib/Seaborn

Docker/Kubernetes

Cloud platforms (OCI/AWS/GCP/AZ)

NLP libraries (SpaCy/NLTK/HF Transformers)

PySpark/Kafka/Airflow

Job description

Howmet Aerospace Inc. in Pittsburgh, PA, is seeking an Artificial Intelligence Engineer to join the Global Information Systems group at the Corporate Center.

You will develop and deploy AI models and related data pipelines, collaborating with data engineers, application developers and analysts. Responsibilities include model development and training, production deployment, API design, data management, and ongoing optimization, with a focus on speed, accuracy and scalability for enterprise