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EY
EY

EY, previously known as Ernst & Young, is a British multinational professional services network based in London, United Kingdom

Experienced AI Engineer/Data Scientist

职能机器学习
级别中级
地点United States
方式现场办公
类型全职
发布2个月前
立即申请

必备技能

Machine Learning

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Your bold ambition is just the beginning!

Join our Data and Analytics Consulting team – help to transform businesses through the power of people, technology, and innovation.

The opportunity

When you join as AI Engineer, you’ll do more than just advise businesses, you’ll collaborate with key decision-makers to help them make better choices. Our team is dedicated to leverage business expertise and cutting-edge technology to solve complex challenges facing our clients. We are currently expanding our capabilities in AI (incl. Generative AI) technologies and are looking for a skilled AI Engineer to join our dynamic team, which works with both public sector institutions and major private companies in the Baltics and beyond.

Your Key Responsibilities

  • Use your expertise in AI, Machine Learning and Advanced Analytics technologies and solutions to advise our clients how to best solve their business challenges.

  • Translate complex technical details and the potential impact of AI technologies into clear, actionable advice for non-technical stakeholders.

  • Design and conduct data science experiments to evaluate models, hypotheses, and algorithms.

  • Design and implement AI solutions using various technologies that address client-specific needs and add tangible value.

  • Act as a liaison between specialised technical teams and business stakeholders.

  • Establish relationships with teams & client personnel at appropriate levels when needed.

  • Develop your professional knowledge and experiences.

  • Possess good business acumen.

Attributes to thrive in the role

  • Bachelor’s, or Master’s degree (preferred) in Data Science, Artificial Intelligence or other relevant fields such as Physics, Mathematics, Economics, Computer Science, Information Systems, or Engineering.

  • Work experience with AI technologies, experience in Natural Language Processing / Natural Language Understanding / Large Language Models / Generative AI.

  • Strong analytical and problem-solving skills, with the ability to apply statistical techniques and Machine Learning algorithms effectively.

  • Knowledge of programming principles and best practices related to software development, AI engineering, MLOps and/or LLMOps (e.g., model versioning, monitoring, continuous training, and deployment automation) with ability to prepare some scripts or prototypes yourself.

  • Ability to look at the AI solution from systemic perspective including data, technology and algorithms.

  • A high level of interpersonal skills for communication and collaboration, ability to lead and promote growth among junior team members.

  • Ability to work with vague requirements from stakeholders and translate them into actionable items.

  • Demonstrated ability to manage projects, including timelines, stakeholders, and deliverables

Attributes that would be advantageous

  • Proficiency in Python and familiarity with AI frameworks and libraries such as Tensor Flow, Py Torch, Scikit-Learn, Streamlit, Num Py, Sci Py and/or similar.

  • Familiarity with AI related frameworks and tools (e.g., Kedro, Kubeflow, Azure ML, Lang Chain, Lang Graph, Azure Foundry, ZenML, and/or similar technologies).

  • Familiarity with building AI solutions using cloud (Microsoft Azure, AWS or GCP).

What we offer:

  • Continuous learning & fast growth: You’ll have access to a wide range of internal and external learning experiences, certifications, and real projects designed to accelerate your development and support your career ambitions.

  • Flexibility & wellbeing: We’ll provide the tools, support, and flexibility, so you can make a meaningful impact, in your own way - hybrid and remote work possibilities, wellbeing programs, team building events, volunteering activities and many more.

  • Comprehensive benefits: include additional health, life, and travel insurance; paid time off for studies, personal development, volunteering, and major life milestones; a mobile services allowance; employee referral bonuses; and access to various discounts and subscriptions.

  • International experience: Work in a truly international environment — from cross-border projects and global initiatives to collaboration with inspiring colleagues across the Baltics and beyond.

  • Transformative leadership: You’ll be supported by leaders who invest in your potential — providing feedback, guidance, and opportunities to grow into the best version of yourself.

  • Diverse and inclusive culture: Be yourself and bring your ideas to the table — your individuality drives our collective strength.

Salary ranges: EUR 3000 – 3600 gross

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关于EY

EY

EY

Public

EY, previously known as Ernst & Young, is a British multinational professional services network based in London, United Kingdom. Along with Deloitte, KPMG and PwC, it is one of the Big Four professional services firms.

10,001+

员工数

London

总部位置

评价

2条评价

2.7

2条评价

工作生活平衡

2.0

薪酬

3.0

企业文化

2.2

职业发展

3.5

管理层

1.8

25%

推荐率

优点

Opportunity to become top performer

Handle large accounts

High responsibility roles

缺点

Long hours and intense work pressure

Poor management and leadership

Burnout issues

薪资范围

31,254个数据点

Mid/L4

Mid/L4 · Operations Research Analyst

1,738份报告

$142,571

年薪总额

基本工资

$136,899

股票

-

奖金

$5,673

$100,128

$203,912

面试评价

7条评价

难度

3.0

/ 5

时长

14-28周

录用率

57%

面试流程

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Technical/Case Interview

5

Partner/Director Interview

6

Offer

常见问题

Behavioral/STAR

Case Study

Technical Knowledge

Past Experience

Culture Fit