Jobs

Lead Engineer, Disciplinary Engineering and Science - Mathematics & Data Science
IT-FI-FLORENCE-VIA FELICE MATTEUCCI 2
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On-site
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Full-time
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5d ago
Required Skills
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:
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Collaborating with multidisciplinary teams in the definition of new AI-Powered Engineering workflows for Product Optimization and Simulation (in terms of performance, manufacturability, controllability)
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Leading technical development of research and development projects on the combination of AI and engineering methodologies.
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Developing and integrating software components for AI applications according to customer and technical requirements
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Checking availability and relevance of internal and external data sources
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Proposing, and leading new data collection activities. Cleaning and validating data
You will work with:
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AI Product Owners to define project technical goals and requirements
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AI Engineers to define the project software architecture and maintenance/retraining strategy
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Engineering Subject Matter Experts to adapt AI technology to the industry needs
Fuel your passion
To be successful in this role you will:
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Have experience in defining the technical requirements and expectations of AI solutions for engineering applications.
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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.
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Have proven experience of applying AI algorithms for dynamical data sources (time series) regression, clustering, anomaly detection and uncertainty quantification.
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Have experience in combining models with data from different sources and hybrid modelling approaches.
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Have experience in defining models for 3D/Graph data types.
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Have proven experience with optimization algorithms (e.g. gradient based, model based, non-parametric for parametric and non-parametric inputs) and active learning.
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Have experience with traditional control algorithms calibration, MPC and RL.
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Have experience in software programming languages including Python, C++
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Demonstrate working knowledge of modern agentic frameworks requirements.
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Proven track record of keeping up-to-date with industry trends and technology developments in the field of AI applied to Engineering.
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Demonstrate working knowledge of model deployment techniques and edge serving.
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Demonstrate working knowledge of turbomachinery thermodynamics, chemistry, rotor dynamic.
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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:
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Occasionally working remotely from home or any other work location
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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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About Baker Hughes

Baker Hughes
PublicBaker 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+
Employees
Houston
Headquarters
Reviews
3.4
10 reviews
Work Life Balance
3.8
Compensation
3.2
Culture
2.9
Career
2.8
Management
2.1
45%
Recommend to a Friend
Pros
Good work-life balance
Great benefits
Good opportunities for growth and mobility
Cons
Poor upper management and leadership issues
Lack of appreciation and respect for employees
Limited advancement opportunities
Salary Ranges
554 data points
L2
L3
L4
L5
L6
Senior/L5
L2 · Business Analyst L2
0 reports
$97,988
total / year
Base
$39,195
Stock
$48,994
Bonus
$9,799
$68,592
$127,384
Interview Experience
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
25%
Experience
Positive 25%
Neutral 50%
Negative 25%
Interview Process
1
Application Review
2
Recruiter Screen
3
Digital/HireVue Interview
4
Technical Interview
5
Hiring Manager Interview
6
Offer
Common Questions
Technical Knowledge
Behavioral/STAR
Past Experience
Problem Solving
Culture Fit
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