Artificial Intelligence Engineer

Basic Qualifications:

• Technical bachelor's degree from an accredited institution
• Minimum of 5 years of experience in Information Technology
• 2+ years prior experience in analytics and/or data science 
• Working knowledge of SQL and Python
• Strong grasp of linear algebra, statistics, optimization techniques, and algorithm design.
• Employees must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.  Visa sponsorship is not available for this position
• Exposure to data engineering/data pipeline development

Preferred Qualifications:

• Bachelor’s degree in data science or artificial intelligence
• Experience using the following python packages
  • Machine Learning - TensorFlow, PyTorch, Scikit-learn, or similar frameworks.
  • Data Manipulation and visualization - Pandas, NumPy, and data visualization libraries such as Matplotlib or Seaborn.
• Familiarity with cloud platforms (Oracle, AWS, Google Cloud, Azure) and deployment tools like Docker and Kubernetes. Specifically, Oracle Cloud Infrastructure a plus.
• Familiarity with integrating cloud technologies with legacy applications
• Creating architecture with network segmentation in mind.
• Experience with NLP libraries such as SpaCy, NLTK, or Hugging Face Transformers is advantageous.
• Exposure to Python data packages and streaming technology, such as PySpark, Kafka, Apache Airflow and delta loading.

Salary Range: $90k - $115k/year approximation (actual compensation is subject to variation due to factors such as education, experience, skillset, and/org location).

Howmet Aerospace Inc. (“Howmet”) is currently in search of an Artificial Intelligence Engineer to join the Global Information Systems (GIS) organization at the Howmet Corporate Center in Pittsburgh, PA.  

In this role you will be responsible for developing and deploying artificial intelligence models and surrounding applications and data pipelines. -

Major activities/Key challenges:

• Model Development and Training

  • Design and build machine learning and deep learning models tailored to solve specific business problems.

  • Train, evaluate, and fine-tune models using appropriate datasets and techniques.

• Application Integration

  • Deploy AI models into production and integrate them with existing systems or applications.

  • Design APIs or interfaces for models to interact with external applications.

• Data Management and pipeline development

  • Collect, preprocess, and clean datasets to ensure data quality and relevance.

  • Create and optimize pipelines for efficient data handling.

• Performance Optimization

  • Monitor the performance of deployed models and update them as needed.

  • Optimize model performance for speed, accuracy, and scalability.

• Research and Innovation

  • Stay updated with the latest AI and machine learning research and integrate new methodologies where applicable.

  • Experiment with state-of-the-art tools and technologies to improve current solutions.

• Collaboration and Communication

  • Work closely with cross-functional teams, including data engineers, application developers and analysts, and business stakeholders.

  • Translate complex AI concepts into actionable business insights.

Essential knowledge, skills and abilities:

• Strong verbal and written communications skills and ability to interact with customers, vendors, other IT professionals, and management; can communicate technical information effectively across all levels of the organization
• Practices continuous learning, interested in learning and mastering new technologies and techniques to improve processes and systems
• Sound decision making, capable of resolving open items swiftly and efficiently
• Strong aptitude to plan and prioritize own work to manage multiple priorities and meet deadlines
• Solid project management and organizational skills including documenting and optimizing processes