Job Description: AI/Machine Learning Engineer – TMT – Manager - Consulting
Introduction
At EY, you’ll have the opportunity to build a career as unique as you are, supported by a global scale, inclusive culture, and cutting-edge technology. Your contribution will help EY become better while you build an exceptional career.
Core Values
- High ethical standards and integrity
- Continuous learning and innovation
The Opportunity
- Join the Artificial Intelligence and Data team to apply advanced technology and techniques.
- Collaborate with clients and diverse teams to solve challenging problems.
- Engage in constant research and development.
- Build knowledge applicable across various projects.
- Influence new ways of working to deliver relevant and innovative solutions.
Key Responsibilities
- Design and build scalable data science and big data solutions.
- Guide and perform technical development tasks.
- Support clients in modern data science, analytics, and software engineering.
- Work within a team of scientists and engineers on complex computational problems.
- Think creatively and collaborate on solution ideation.
Skills and Attributes for Success
- Technical guidance and knowledge sharing.
- Focus on quality and complex issues.
- Demonstrate technical capabilities.
- Active learning about EY and service lines.
Required Qualifications
- Bachelor’s degree with 6-10 years of experience in AI, Data Science, or Machine Learning.
- 2-4 years of experience managing technical teams.
- Extensive experience in telecommunications, media, or technology sectors.
- Proficiency in Python.
- Experience with Generative AI models (e.g., OpenAI, LLMs, DALL-E, LlamaIndex, Langchain, RAG).
- Experience with ML libraries (scikit-learn, PyTorch, ONNX).
- Experience with DevOps (GIT, Azure DevOps) and Agile tools (Jira).
- Knowledge of telecommunications protocols (5G, LTE).
- Experience analyzing large datasets.
- Familiarity with streaming media and multi-modal models.
- Understanding of customer segmentation, churn prediction, and recommendation systems.
- Knowledge of regulatory considerations in TMT.
- Experience with real-time data processing (e.g., Kafka).
- Cloud familiarity (AWS, Azure).
- Network optimization algorithms and emerging tech (Edge, IoT).
- Strong mathematical skills.
- Willingness to travel.
Preferred Qualifications
- Deep understanding and ability to teach various concepts.
- Master’s degree in relevant fields.
- Skills in languages beyond Python.
- Experience in fine-tuning Generative AI models.
Personal Attributes
- Agile and growth-oriented mindset.
- Curious and purpose-driven.
- Inclusive and valuing diversity.
Benefits
- Competitive compensation based on performance.
- Salary ranges: $141,400 - $259,200 (US), $169,700 - $294,600 (certain states).
- Total Rewards include health coverage, pension, 401(k), paid time off.
- Hybrid working model.
- Flexible vacation and paid holidays.
- Opportunities for continuous learning and leadership.
Application Process
- EY accepts applications ongoing.
- Contact promptly if meeting criteria.
About EY
- Committed to building a better working world.
- Operating in over 150 countries.
- Diverse services across assurance, consulting, law, strategy, tax, and transactions.
Equal Opportunity Statement
- EY provides equal employment opportunities and accommodations.
# Job Highlights
Qualifications:
- Advanced degrees or equivalent experience
- 6-10 years in AI/Data Science/ML
- Management experience
- Telecom/Media/Tech experience
- Skills in Python, ML libraries, Generative AI frameworks
- Experience with DevOps and Agile tools
- Experience with large datasets, network protocols, streaming media, multi-modal models
- Cloud and real-time data processing familiarity
- Mathematical and quantitative skills
- Languages beyond Python
- AI model fine-tuning
Benefits:
- Competitive salary and performance rewards
- Health coverage, 401(k), paid time off
- Flexible, hybrid work environment
- Continuous learning opportunities
Responsibilities:
- Collaborate with clients and teams
- Design and scale data solutions
- Guide technical development
- Engage in research, innovation, and solution implementation
- Share knowledge and provide technical guidance
- Maintain high-quality service and technical practices