Work smart, have fun and make an impact!
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 DescriptionWe are looking for a highly motivated Senior AI/ML Engineer to join our growing AI Center of Excellence, responsible for using AI and machine learning to drive innovation across the organization.
Your responsibilities will include (but will not be limited to):
Leverage data to solve business problems of various business units at EcoVadis
Design, develop, deploy and maintain scalable AI/ML systems
Design AI/ML pipelines by applying the best practices in MLOps / LLMOps / AgentOps
Build AI/ML engineering infrastructure and systems to orchestrate batch and real-time pipelines
Run large-scale experiments and tests to ensure quality and efficiency of ML and data pipelines
Partner with scientists and engineers to make AI/ML models accessible to end-users and downstream processes
Leverage Python, MLflow, Azure stack (e.g., Azure cloud, Azure ML, Azure Foundry) and Databricks to deliver end-to-end solutions
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
Industry experience in driving, designing and implementing production-grade AI/ML systems and integrating those into business applications as well as model monitoring at scale
Strong programming skills in Python and related ML libraries
Strong experience of AI/ML lifecycle, principles, and MLOps / LLMOps / AgentOps tooling (e.g., MLflow, LangChain, VectorDBs, Evaluation frameworks, etc)
Experience in cloud technology, preferably Azure and its ecosystem (e.g., Azure Foundry, Azure Bicep, AzureML and Azure Cloud Storage) and Databricks
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 with REST API for ML model serving
Experience with Docker and container orchestration
Experience with relational and non-relational databases
Experience in cross-functional collaboration in the development of AI/ML products and services (e.g., Engineers, Product Managers)
Contribution to open-source libraries is a plus
Offer available only for candidates eligible to work and live in Spain
Location: Hybrid in Barcelona (2 days per week in the office) / Full remote from Spain
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
- Remote work from abroad policy
- Meals and Transportation Vouchers (Coverflex 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, 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 from a diverse and skilled talent pool, 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).
Our recruitment processes do not include AI systems that make autonomous decisions impacting individuals’ rights without human oversight. Inputs and outputs of the system have been validated by humans and answers are based on algorithms that analyze previous data with which the system has been trained. We use SmartRecruiters as our applicant tracking system and to schedule interviews. Gemini is used to summarize notes from interviews and to refine job descriptions and social media messaging. AssessFirst is used to support talent assessment decisions.
