Sure. Here's the analysis:

Job Analysis:

The role of AI & Machine Learning Engineer at EY is fundamentally about leveraging cutting-edge technology and innovative thinking to solve complex business problems for clients in the telecommunications, media, and technology (TMT) sector. In this position, the candidate will not only implement scalable AI systems but also ensure that the underlying data pipelines are robust, accurate, and optimized for diverse operational contexts. The expectation is for the candidate to engage heavily with clients, guiding them toward effective solutions amid the fast-paced, evolving landscape of AI and data science. Success in this role means not only technical proficiency but also the ability to lead teams, communicate effectively, and cultivate client relationships while continuously improving models and solutions. The candidate should anticipate navigating challenges such as ambiguity in uncharted problems and managing diverse stakeholder expectations, all while delivering high-quality results that align with both client needs and EY’s strategic objectives.

Company Analysis:

EY operates as a leader in the professional services sector, particularly known for its consulting and technology-focused offerings. The company’s commitment to shaping a better working world signifies a strong mission-oriented culture that prioritizes trust, innovation, and collaboration. In this environment, the AI & Machine Learning Engineer will find themselves in a dynamic setting that values continuous learning and adaptability due to rapid advancements in technology. Furthermore, as a manager, this role will involve considerable visibility, directly interacting with clients and managing project dynamics within a diverse team. EY's global reach and diverse service offerings enable the role to have a broad impact, making it important for candidates to align with the company's values, drive for excellence, and commitment to sustainability. The role is strategically significant, aimed at enhancing EY's capacity to deliver advanced AI solutions that resonate with the evolving demands of clients in a competitive marketplace.

Absolutely. Here are some mock interview questions that could come up:

Tell me about a time when you had to lead a project involving a complex technical problem. What approach did you take, and what was the outcome?
Can you provide an example of how you improved a data processing pipeline in a previous role? What specific technologies did you use?
Describe a situation where you had to manage a diverse team to achieve a common goal. How did you ensure collaboration and maintain team morale?
What methods do you use to stay updated on emerging technologies and industry trends, particularly in AI and Machine Learning?
How would you approach designing a machine learning model for customer churn prediction in a telecommunications context?
What experience do you have with real-time data processing frameworks like Apache Kafka, and how have you applied them in your previous projects?
Imagine you are faced with a scenario where a deployed model is underperforming. What steps would you take to diagnose and resolve the issue?
As a manager, how would you handle a conflict between team members concerning the direction of a project?
Why are you interested in working at EY specifically, and how do you believe your values align with the company’s mission?
Can you describe a challenging client interaction you faced? How did you handle it, and what was the result?
What are some key regulatory considerations you think are important in the TMT sector when implementing AI solutions?
How do you prioritize competing project deadlines while ensuring quality in your team's deliverables?
What would you like to explore further about our team structure and project management processes at EY?
In your opinion, what is the most exciting emerging technology in AI today, and how do you see it impacting the industry?
What questions do you have about EY's commitment to continuous learning and development for its employees?

AI & Machine Learning Engineer Manager

$124.3k/y-$227.9k/y

2 days ago

Highlight

HybridFull-time6+ yearsSenior

Summary

EY is seeking an AI & Machine Learning Engineer - TMT - Manager - Consulting to join their team in Miami, FL. The role involves researching, building, and implementing scalable AI systems tailored to business requirements across various environments.

About the Role

As a Manager in AI Native Engineering, you will deliver innovative solutions that drive business success, work with a variety of clients to deliver the latest data science and big data technologies, and lead teams to design and build scalable solutions. You will engage actively with clients, manage professional employees, and identify opportunities for additional services.

About You

Required:

Bachelor’s degree (4-year degree).
6-10 years of relevant experience in AI, Data Science, and/or Machine Learning.
2-4 years of experience directly managing technical teams.
Strong skills in Python.
Extensive experience in telecommunications, media, or technology sectors.
Proven ability to design and implement machine learning solutions.
Familiarity with telecommunications protocols (e.g., 5G, LTE).
Experience analyzing large-scale datasets from telecommunications networks.
Knowledge of streaming video and audio technologies.
Experience with multi-modal models, including vision-language models.
Understanding of customer segmentation, churn prediction, and recommendation systems.
Knowledge of regulatory and compliance considerations specific to the TMT sector.
Experience with real-time data processing frameworks (e.g., Apache Kafka).
Familiarity with cloud-based telecommunications solutions (e.g., AWS, Azure).
Experience with network optimization algorithms and techniques.
Knowledge of emerging technologies such as edge computing and IoT.
Experience using Generative AI models and frameworks.
Experience with popular ML packages such as scikit-learn, Pytorch, and ONNX.
Extensive experience using DevOps tools like GIT, Azure Devops, and Agile tools such as Jira.
A solid understanding of Machine Learning workflows.
Experience with MLOps methods and platforms such as MLFlow.
Experience with CI/CD and test-driven development.
Experience designing, building, and maintaining ML models, frameworks, and pipelines.
Experience designing and deploying end-to-end ML workflows on major cloud computing platforms.
Understanding of data structures, data modelling, and software engineering best practices.
Proficiency using data manipulation tools and libraries such as SQL, Pandas, and Spark.
Clearly communicating findings, recommendations, and opportunities.
Experience with containerization and scaling models.
Integrating models and feedback from downstream consumption systems.
Deep Learning expertise.
Proficiency in Mathematics, Statistics, and Operations Research.
Experience with Machine Learning techniques.
Knowledge of Data Architecture Design and Modelling.
Familiarity with Cloud Computing environments.
Skills in Technical Design Optimization.
Experience with Continuous Integration and Continuous Delivery/Deployment.
Understanding of Natural Language Processing and Generation.
Knowledge in Image Processing and Analysis.
Skills in Speech and Audio Processing and Analysis.
Ability to scale models effectively.
Strong relationship-building skills.
Demonstrated client trust and value.
Effective communication skills with impact.
Digital fluency and emotional agility.
Experience in hybrid collaboration.
Commercial acumen and negotiation skills.
Proven ability to lead teams and manage change.
Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
Willingness to travel to meet client obligations.

Preferred:

A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches.
Master's degree in Computer Science, Mathematics, Physical Sciences, or other quantitative field.
Experience working with diverse teams to deliver complex solutions.
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C.
Experience fine-tuning Generative AI models.
Experience in managing complex projects with multiple stakeholders.
A strong understanding of industry trends and emerging technologies.
Skills in data visualization and storytelling with data.

Benefits

Comprehensive compensation and benefits package.
Base salary range in the US: $124k–$227.9k.
Base salary range in New York City Metro Area, Washington State, and California (excluding Sacramento): $149.2k–$259k.
Medical and dental coverage.
Pension and 401(k) plans.
Wide range of paid time off options.
Flexible vacation policy.
Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence.

EY is building a better working world by creating new value for clients, people, society, the planet, while building trust in the capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams in more than 150 countries work across a full spectrum of services in assurance, consulting, tax, strategy and transactions, strengthened by sector experience and diverse ecosystem partners.

Find out more about the EY global network: http://ey.com/en_gl/legal-statement

Miami, FL