Machine Learning Engineer

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. If you have questions about the company or open roles you can chat with an insider.

Job Description

We are looking for a highly motivated 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.  Join us! 

Your global responsibilities will include (but will not be limited to):

• Leverage data to solve business problems of various business units at EcoVadis

• Design, develop and maintain scalable ML systems

• Ensure ML lifecycle monitoring by applying the best practices in MLOps and green IT

• Engage in building ML engineering infrastructure and systems to orchestrate batch and streaming pipelines, and leverage Infrastructure as Code (IaC) to manage and provision infrastructure

• Partner with scientists and engineers to make ML models accessible to end-users and downstream processes

• Build and enhance feature stores

• Leverage Python, MLflow,  Azure stack (e.g., Azure cloud, Azure ML, Azure Data Factory) and Databricks to deliver end-to-end solutions

Qualifications

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. 

• M.S. Degree in Computer Science, Mathematics, Engineering, or a related technical discipline

• Demonstrable experience in designing ML systems and integrating those into business applications

• Excellent knowledge of Python, other languages are a plus

• Deep knowledge of machine learning lifecycle, principles, and tooling

• Experience in cloud technology, preferably Azure and its ecosystem (e.g., Azure Data Factory, Azure Bicep)

• Solid understanding of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

• Experience in Linux OS and scripting

• Knowledge of data management fundamentals and data storage principles

• Experience of cross-functional collaboration in the development of ML products and services (e.g., Engineers, Product Managers) is a plus

• Familiarity with (non) relational databases

Bonus

• Contribution to open-source libraries is a plus

• Knowledge of other languages, ecosystems, and CI/CD tools, experience with docker and container orchestration

Additional Information

• Location: Barcelona
• Contract: Permanent

Our growing team in Spain is full of talented professionals from various fields who all share a desire to make sustainability real. We offer competitive salaries and support personal growth from day one. This includes extensive onboarding, teammates' support and a brand new e-learning platform bursting with courses and modules. So you can learn new skills and fine-tune old ones!

Benefits:

• International and very friendly work environment
• Hybrid for colleagues who live near our offices (4 days per month) otherwise remote in the country you were hired in
• Flexible working hours
• Home office allowance program
• IT equipment allowance
• 90 days Working from anywhere policy
• Meals and Transportation Vouchers (Cobee card)
• Health, Wellness, and Dental Benefits
• Unlimited and completely confidential sessions with psychologists and online well-being programs.
• Employee referral bonus policy
• Paid employee volunteer day
• Paid moving day ( 1/year)
• Access to online learning library
• Virtual and in-person team building events
• Co working space with various services + opportunity to work in different locations (Europe and International)

Our hiring team looks forward to reviewing your CV, in English, 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)