Mid-Level Machine Learning Engineer
EcoVadis
Full-time
On-site
Barcelona Catalunya Spain
GreenTech Jobs
Company Description
Work smart, have fun and make an impact!
Our purpose is to guide all companies toward a sustainable world. EcoVadis is the leading provider of business sustainability ratings. Our solutions are backed by an international team of experts and powerful technology. We analyze data and build sustainability scorecards that give companies actionable insights into their environmental, social and ethical risks.
Why apply to EcoVadis? Be a part of the global sustainability change in business. Grow your career. Work with extraordinary people. Feel valued for your contribution.
Learn more about our team and culture on EcoVadis careers page.
Job Description
We are looking for a highly motivated Mid-level Machine Learning (ML) Engineer to join our growing AI Center of Excellence, responsible for using machine learning to drive innovation across the organization. We welcome applications from Spain (office: Barcelona) with an option of remote work.
Your global responsibilities will include (but will not be limited to):
Leverage data to solve business problems of various business units at EcoVadis
Experiment, deploy and maintain ML models by ensuring scalability and speed
Design ML pipelines by applying the best practices in MLOps
Build ML engineering infrastructure and systems to orchestrate batch and real-time pipelines
Partner with scientists and engineers to make ML models accessible to end-users and downstream processes
Leverage Python, MLflow, Azure stack (e.g., Azure cloud, Azure ML, Azure Data Factory) and Databricks to deliver end-to-end solutions
Qualifications
Who we are looking for
You have an outgoing personality along with an exceptional level of drive and a desire to pursue a career in an international and dynamic environment. You also possess excellent verbal and written communication, critical thinking and analytical skills.
Degree in Computer Science, Mathematics, Engineering, or a related technical discipline
Strong programming skills in Python as well as related ML libraries
Industry experience on production-grade end to end ML projects (2 years)
Knowledge of machine learning lifecycle, principles, and MLOps tooling (e.g. MLFlow, Kubeflow)
Experience with REST API for ML model serving
Understanding of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, CI/CD tools and operations
Familiarity with cloud technology, preferably Azure
Experience with docker and container orchestration
Bonus
Contribution to the open-source libraries is a plus
Knowledge of data versioning tools (e.g. DVC)
Additional Information
Location: Barcelona
Start date: May 2025
In return for your expertise, we offer:
Support with all the necessary office and IT equipment
Flexible working hours
Wellness allowance for mental and physical wellbeing
Access to professional mental health support
Referral bonus policy
Learning and development
Sustainability events and community involvement
Peer recognition program
Employee-led resource groups
Hybrid work organization (from the office or from home)
Remote work from abroad policy
Meals and Transportation Vouchers (Cobee card)
Dental Benefits
Life & Accident Insurance + Private Health Insurance
Paid employee volunteer day
Paid moving day (1/year)
Time off: 1 Community Service Day + 1 Personal Day
Summer Hours in July and August (36 hours per week)
Hybrid Monthly Allowance for electricity and Internet
Our hiring team looks forward to reviewing your CV and cover letter with a guaranteed response to every application. A new job with purpose awaits you!
Don’t fit all the criteria but still think you’d be a good candidate? Please apply anyway to give our hiring team the opportunity to assess your skills and to learn more about what you could bring to EcoVadis. We’re interested in hiring capable people, regardless of professional and educational background.
Can the hiring process be adjusted to suit my needs? Yes. We want everyone going through the hiring process with EcoVadis to feel confident that you are able to demonstrate your full potential. We welcome applications from disabled people, people with long-term health conditions, and neurodiverse candidates. If you need any adjustments, including the provision of interview questions, please let the hiring team know.
Our team’s strength comes from everyone’s uniqueness and is founded upon mutual respect. EcoVadis commits to equity, inclusion and reducing bias in our hiring processes. EcoVadis does not accept any form of discrimination based on color, national or ethnic origin, ancestry, citizenship, religion, beliefs, age, sex, gender identity, sexual orientation, neurodiversity, disability, parental status, or any other protected characteristic that makes you unique. In your application, we encourage you to remove personal information such as: photographs, marital status, number of children, religion, gender, residential postal code, university graduation date, past medical or parental leave(s) taken, nationality (instead, please state if you are legally eligible to work in the job region/country), university name (instead, please state any degrees obtained and the study major).
Work smart, have fun and make an impact!
Our purpose is to guide all companies toward a sustainable world. EcoVadis is the leading provider of business sustainability ratings. Our solutions are backed by an international team of experts and powerful technology. We analyze data and build sustainability scorecards that give companies actionable insights into their environmental, social and ethical risks.
Why apply to EcoVadis? Be a part of the global sustainability change in business. Grow your career. Work with extraordinary people. Feel valued for your contribution.
Learn more about our team and culture on EcoVadis careers page.
Job Description
We are looking for a highly motivated Mid-level Machine Learning (ML) Engineer to join our growing AI Center of Excellence, responsible for using machine learning to drive innovation across the organization. We welcome applications from Spain (office: Barcelona) with an option of remote work.
Your global responsibilities will include (but will not be limited to):
Leverage data to solve business problems of various business units at EcoVadis
Experiment, deploy and maintain ML models by ensuring scalability and speed
Design ML pipelines by applying the best practices in MLOps
Build ML engineering infrastructure and systems to orchestrate batch and real-time pipelines
Partner with scientists and engineers to make ML models accessible to end-users and downstream processes
Leverage Python, MLflow, Azure stack (e.g., Azure cloud, Azure ML, Azure Data Factory) and Databricks to deliver end-to-end solutions
Qualifications
Who we are looking for
You have an outgoing personality along with an exceptional level of drive and a desire to pursue a career in an international and dynamic environment. You also possess excellent verbal and written communication, critical thinking and analytical skills.
Degree in Computer Science, Mathematics, Engineering, or a related technical discipline
Strong programming skills in Python as well as related ML libraries
Industry experience on production-grade end to end ML projects (2 years)
Knowledge of machine learning lifecycle, principles, and MLOps tooling (e.g. MLFlow, Kubeflow)
Experience with REST API for ML model serving
Understanding of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, CI/CD tools and operations
Familiarity with cloud technology, preferably Azure
Experience with docker and container orchestration
Bonus
Contribution to the open-source libraries is a plus
Knowledge of data versioning tools (e.g. DVC)
Additional Information
Location: Barcelona
Start date: May 2025
In return for your expertise, we offer:
Support with all the necessary office and IT equipment
Flexible working hours
Wellness allowance for mental and physical wellbeing
Access to professional mental health support
Referral bonus policy
Learning and development
Sustainability events and community involvement
Peer recognition program
Employee-led resource groups
Hybrid work organization (from the office or from home)
Remote work from abroad policy
Meals and Transportation Vouchers (Cobee card)
Dental Benefits
Life & Accident Insurance + Private Health Insurance
Paid employee volunteer day
Paid moving day (1/year)
Time off: 1 Community Service Day + 1 Personal Day
Summer Hours in July and August (36 hours per week)
Hybrid Monthly Allowance for electricity and Internet
Our hiring team looks forward to reviewing your CV and cover letter with a guaranteed response to every application. A new job with purpose awaits you!
Don’t fit all the criteria but still think you’d be a good candidate? Please apply anyway to give our hiring team the opportunity to assess your skills and to learn more about what you could bring to EcoVadis. We’re interested in hiring capable people, regardless of professional and educational background.
Can the hiring process be adjusted to suit my needs? Yes. We want everyone going through the hiring process with EcoVadis to feel confident that you are able to demonstrate your full potential. We welcome applications from disabled people, people with long-term health conditions, and neurodiverse candidates. If you need any adjustments, including the provision of interview questions, please let the hiring team know.
Our team’s strength comes from everyone’s uniqueness and is founded upon mutual respect. EcoVadis commits to equity, inclusion and reducing bias in our hiring processes. EcoVadis does not accept any form of discrimination based on color, national or ethnic origin, ancestry, citizenship, religion, beliefs, age, sex, gender identity, sexual orientation, neurodiversity, disability, parental status, or any other protected characteristic that makes you unique. In your application, we encourage you to remove personal information such as: photographs, marital status, number of children, religion, gender, residential postal code, university graduation date, past medical or parental leave(s) taken, nationality (instead, please state if you are legally eligible to work in the job region/country), university name (instead, please state any degrees obtained and the study major).