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About the Role

As an AI Engineer within the Internal Firm Services practice, you will transform raw data into actionable insights using data, algorithms, and software engineering to build and deploy AI and Machine Learning solutions at scale. You will analyze complex problems, mentor others, and maintain professional standards, focusing on building relationships and understanding business context. This role involves designing AI systems, data wrangling, and implementing software to make AI models useful and scalable, anticipating team needs, and delivering quality solutions in complex situations. You will embrace ambiguity for growth, deepen technical skills, and contribute to business strategies.

Responsibilities

• Design and implement AI systems to transform raw data into actionable insights
• Develop scalable machine learning models using Python and TensorFlow
• Integrate data from diverse sources to support AI and machine learning solutions
• Conduct complex data analysis to identify patterns and trends for informed decision-making
• Collaborate with internal teams to enhance data infrastructure and integration processes
• Utilize natural language processing techniques to improve text analytics and sentiment analysis
• Apply deep learning and neural network methodologies to optimize AI model performance
• Manage data pipelines to validate efficient data flow and processing
• Build and maintain relationships with stakeholders to align AI initiatives with business objectives
• Mentor junior team members in AI implementation and data engineering practices

Requirements

• At least a Bachelor's degree or, in lieu of a degree, demonstrating in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in Engineering with AI and Machine Learning for each missing year of college is required
• At least 2 years of experience
• Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials
• Proficiency in Python and TensorFlow
• Ability to navigate ambiguity with critical thinking and problem-solving
• Ability to build meaningful client connections and manage relationships

Skills

• AI implementation
• Machine learning libraries
• Complex data analysis
• Data modeling
• Python
• TensorFlow
• Natural language processing
• Deep learning
• Neural networks
• Data engineering

Location

• Up to 20% travel

Work Type

• Full-time

Experience Level

• Senior Associate
• At least 2 years of experience

Education Level

• Bachelor's degree

Salary/Compensations

• $55,000 - $151,470
• $55,000 - $187,000 for Washington state residents

Benefits

• Medical
• Dental
• Vision
• 401k
• Holiday pay
• Vacation
• Personal and family sick leave
• Annual discretionary bonus

About the Company

• PwC is an equal opportunity employer.
• Learn more about how we work: https://pwc.to/how-we-work

Equal Opportunity

• All qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.
• PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.
• For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws.
• At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.