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Baker Hughes
Baker Hughes

Baker Hughes Company is an American global energy technology company co-headquartered in Houston, Texas and London, UK

Lead Engineer, Disciplinary Engineering and Science - Mathematics & Data Science

职能机器学习
级别Lead级
地点IT-FI-FLORENCE-VIA FELICE MATTEUCCI 2
方式现场办公
类型全职
发布1个月前
立即申请

必备技能

Machine Learning

Are you passionate about AI applied to Design and Controls?

Do you enjoy collaborating with multidisciplinary teams to solve complex problems?

Join our Artificial Intelligence & Development team:

Our team provides industry-leading products and services that optimize the production and processing of energy. You will contribute to our future as an AI player in the Energy Transformation industry.

We implement and adapt AI algorithms across a broad variety of projects. These include predictive maintenance and defect detection, control and robotics, design optimization and simulation, unmanned inspections and many others. Our team deploys production-ready code in Cloud and Edge environments to make energy products more efficient, reliable, safe and sustainable.

Partner with the best

You will be instrumental in our mission to make energy safer, cleaner and more efficient through intelligent technologies. If you have Simulation and Controls background and AI experience, we would like to hear from you.

As Lead AI Specialist for engineering and controls, you will be responsible for:

  • Collaborating with multidisciplinary teams in the definition of new AI-Powered Engineering workflows for Product Optimization and Simulation (in terms of performance, manufacturability, controllability)

  • Leading technical development of research and development projects on the combination of AI and engineering methodologies.

  • Developing and integrating software components for AI applications according to customer and technical requirements

  • Checking availability and relevance of internal and external data sources

  • Proposing, and leading new data collection activities. Cleaning and validating data

You will work with:

  • AI Product Owners to define project technical goals and requirements

  • AI Engineers to define the project software architecture and maintenance/retraining strategy

  • Engineering Subject Matter Experts to adapt AI technology to the industry needs

Fuel your passion

To be successful in this role you will:

  • Have experience in defining the technical requirements and expectations of AI solutions for engineering applications.

  • Have deep understanding of Machine Learning and AI algorithms for regression, classification and anomaly detection tasks applied to tabular data with uncertainty quantification and explainability requirements.

  • Have proven experience of applying AI algorithms for dynamical data sources (time series) regression, clustering, anomaly detection and uncertainty quantification.

  • Have experience in combining models with data from different sources and hybrid modelling approaches.

  • Have experience in defining models for 3D/Graph data types.

  • Have proven experience with optimization algorithms (e.g. gradient based, model based, non-parametric for parametric and non-parametric inputs) and active learning.

  • Have experience with traditional control algorithms calibration, MPC and RL.

  • Have experience in software programming languages including Python, C++

  • Demonstrate working knowledge of modern agentic frameworks requirements.

  • Proven track record of keeping up-to-date with industry trends and technology developments in the field of AI applied to Engineering.

  • Demonstrate working knowledge of model deployment techniques and edge serving.

  • Demonstrate working knowledge of turbomachinery thermodynamics, chemistry, rotor dynamic.

  • Demonstrate working knowledge in databases, Test Driven Development and Agile Development methods.

Work in a way that works for you

We recognize that everyone is different and that the way in which people want to work and deliver at their best is different for everyone too. In this role, we can offer the following flexible working patterns:

  • Occasionally working remotely from home or any other work location

  • Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive

The Virtual Port:

This is remote role, with occasional travel to one of our local virtual ports.

We want to play a role in the energy transition through the acceleration of digital transformation and the application of intelligent technologies. To make this vision a reality, we need people who are creative, curious and eager to change the world.

We are convinced that freedom and diversity in ideas and experiences are the main drivers of innovation.

We are a group of passionate sailors who appreciate freedom, opportunity, and risk. Our offices are like ports of call, ready to welcome our team and facilitate sharing experiences. If you share our vision, we would like to hear from you.

The Baker Hughes internal title for this role is: Lead Engineer, Mathematics & Data Science, Disciplinary Engineering and Science

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关于Baker Hughes

Baker Hughes

Baker Hughes is a global energy technology company that provides solutions for energy and industrial customers worldwide. The company offers equipment, services, and digital solutions for oil and gas operations, industrial processes, and energy transition technologies.

10,001+

员工数

Houston

总部位置

$13.9B

企业估值

评价

10条评价

3.7

10条评价

工作生活平衡

2.8

薪酬

4.0

企业文化

4.2

职业发展

3.5

管理层

3.2

68%

推荐率

优点

Supportive management and great team culture

Excellent benefits and competitive compensation

Professional development and training opportunities

缺点

Heavy workload and frequent overtime

High-pressure and stressful environment

Poor work-life balance

薪资范围

262个数据点

L2

L6

Mid/L4

Senior/L5

L3

L4

L5

L2 · Data Scientist L2

0份报告

$23,927

年薪总额

基本工资

$9,571

股票

$11,964

奖金

$2,393

$16,749

$31,105

面试评价

4条评价

难度

3.0

/ 5

时长

14-28周

录用率

25%

体验

正面 25%

中性 50%

负面 25%

面试流程

1

Application Review

2

Recruiter Screen

3

Digital/HireVue Interview

4

Technical Interview

5

Hiring Manager Interview

6

Offer

常见问题

Technical Knowledge

Behavioral/STAR

Past Experience

Problem Solving

Culture Fit