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Mid-Level 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.

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 or Remote from Spain
  • 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).

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Average salary estimate

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What You Should Know About Mid-Level Machine Learning Engineer, EcoVadis

Join EcoVadis as a Mid-Level Machine Learning Engineer in vibrant Barcelona and be part of a team committed to making a tangible impact on sustainability! In this role, you'll dive deeply into exciting projects, leveraging machine learning to transform data into actionable insights for various business units. You'll not just deploy and maintain ML models, but also design ML pipelines following MLOps best practices, ensuring both speed and scalability. Collaborating with a passionate group of scientists and engineers, you will create accessible ML solutions that empower our organization. Your technical skills in Python, familiarity with Azure stack, and experience in end-to-end ML projects will set you up for success. EcoVadis promotes a culture of innovation and learning, offers flexible working options, and values your contributions. Plus, you get to work in an inclusive environment where everyone's uniqueness is celebrated and embraced. Ready to grow your career? Let’s make a difference together at EcoVadis!

Frequently Asked Questions (FAQs) for Mid-Level Machine Learning Engineer Role at EcoVadis
What are the key responsibilities of a Mid-Level Machine Learning Engineer at EcoVadis?

As a Mid-Level Machine Learning Engineer at EcoVadis, your main responsibilities include leveraging data to solve business problems, experimenting with and deploying machine learning models, and ensuring they are scalable and efficient. You'll also design ML pipelines, and build engineering infrastructure for both batch and real-time processing, collaborating closely with scientists and engineers to enhance model accessibility.

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What qualifications are needed to become a Mid-Level Machine Learning Engineer at EcoVadis?

To qualify as a Mid-Level Machine Learning Engineer at EcoVadis, candidates should hold a degree in Computer Science, Mathematics, Engineering, or a related field. You should have industry experience with production-grade ML projects and strong programming skills in Python, particularly with various ML libraries and frameworks.

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How does EcoVadis support the professional growth of its Mid-Level Machine Learning Engineers?

At EcoVadis, we value continuous learning and provide ample opportunities for professional development, including access to training programs, participation in sustainability events, and peer recognition initiatives. We encourage our Mid-Level Machine Learning Engineers to grow their expertise and engage in a culture of innovation.

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What types of technologies do Mid-Level Machine Learning Engineers at EcoVadis use?

Mid-Level Machine Learning Engineers at EcoVadis utilize a range of technologies including Python, Azure stack, MLflow, and Databricks. Familiarity with REST APIs for ML model serving, container orchestration using Docker, and MLOps tools are also key components of the role.

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What is the work culture like for Mid-Level Machine Learning Engineers at EcoVadis?

The work culture at EcoVadis is dynamic, inclusive, and built on mutual respect. Mid-Level Machine Learning Engineers have the flexibility to work remotely and are encouraged to contribute to sustainability initiatives while collaborating with diverse teams in an atmosphere that celebrates uniqueness and inclusion.

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Common Interview Questions for Mid-Level Machine Learning Engineer
What experience do you have with deploying machine learning models?

When answering this question, highlight specific projects where you successfully deployed machine learning models, detailing the technologies you used and the outcomes. Discuss your understanding of the ML lifecycle and MLOps tooling, as these are crucial for the role at EcoVadis.

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How do you ensure that your ML models are scalable?

You should emphasize your experience with model optimization techniques and best practices in MLOps, discussing how you've applied them in previous projects. Demonstrating an understanding of monitoring model performance post-deployment can also show your keen insights into scalability.

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Can you explain your experience working with Python and ML libraries?

Detail your programming experience with Python, mentioning the specific libraries you've used, such as TensorFlow or Scikit-Learn. Discuss how you've applied these libraries in real-world applications, underscoring your ability to contribute to EcoVadis's objectives.

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What strategies do you employ to collaborate with data scientists and engineers?

Talk about the importance of clear communication and teamwork. Offer examples of how you’ve successfully partnered with other tech teams to ensure that ML models are integrated seamlessly into broader systems. This reflects well on your collaborative nature, which is valued at EcoVadis.

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What do you understand about MLOps, and how have you implemented it?

In your response, define MLOps and discuss your experience implementing it in your projects. Highlight specific tools like MLflow or Kubeflow that you've used, emphasizing how these practices improved the lifecycle of your ML projects.

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Describe your familiarity with REST APIs for ML model serving.

Explain your understanding of REST APIs and your experience employing them to serve machine learning models. Discuss any projects where you’ve successfully integrated an API for model deployment, showcasing your practical expertise in this critical area.

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How do you approach troubleshooting ML models that don’t perform as expected?

Describe your systematic approach to identifying issues in underperforming ML models, such as analyzing input data, hyperparameters, and output predictions. Mention any specific experiences that illustrate your problem-solving skills in this context.

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What do you think is key to successful teamwork in projects involving machine learning?

Stress the importance of clear communication, shared goals, and respect for each team member’s expertise. You might also discuss how you adapt your communication style to fit the audience, ensuring everyone is on the same page.

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Can you provide an example of a batch processing pipeline you've built?

Share a specific example of a batch processing pipeline you built, including the technologies used and the overall impact on efficiency or performance. Be sure to relate it back to the skills and experiences relevant to the Mid-Level Machine Learning Engineer position at EcoVadis.

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What motivates you to work in the field of machine learning?

In your response, connect your personal passion for technology and sustainability to EcoVadis’s mission. Discuss how your interest in innovation drives you to stay updated with the latest advancements in machine learning, which is crucial for an effective contribution to EcoVadis.

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EcoVadis' purpose is to guide all companies toward a sustainable world. We envision a global marketplace where sustainability intelligence influences every business decision – improving economies, people’s lives and the planet we all depend on. ...

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DATE POSTED
April 10, 2025

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