AI Engineer

Ecolab Quimica Ltda.; Kraków; Hybrid; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Lunch subsidy

Sport bonus

Holiday bonus

Job summary

Ecolab is seeking a highly skilled AI Engineer to design, develop, and deploy AI-powered solutions with a focus on agentic AI systems on Azure cloud infrastructure. The role requires hands-on experience with AI/ML models, LLMs, and scalable production deployments in a hybrid work model.

Responsibilities include building agent-based AI applications, data processing with Azure Databricks, and implementing CI/CD pipelines.

Qualifications

• 2–5 years of experience in AI/ML engineering or data science.
• Strong programming skills in Python and SQL.
• Experience with Azure cloud services (Azure OpenAI, Azure ML, Functions, Storage, Key Vault).
• Hands‑on experience with Azure Databricks / PySpark for data processing.
• Familiarity with CI/CD pipelines (Azure DevOps or GitHub Actions).
• Basic understanding of containerization (Docker).
• Strong foundation in Machine Learning and Deep Learning.
• Experience with large language models (LLMs) and prompt engineering.
• Understanding of: Retrieval-Augmented Generation (RAG).
• Embeddings and vector search.
• Transformer-based models.
• Exposure to agentic AI concepts / multi-agent workflows.
• Experience with ML frameworks: Scikit-learn, TensorFlow, PyTorch, or Transformers.

Responsibilities

• Design and develop AI-powered applications and agent-based systems for intelligent automation and decision‑making.
• Build and deploy AI/ML solutions using Azure services (Azure OpenAI, Azure Functions, Azure ML, Cognitive Services).
• Develop data processing and ML workflows using Azure Databricks and Apache Spark.
• Implement and manage CI/CD pipelines using Azure DevOps or GitHub Actions for automated deployment.
• Work on LLM-based solutions, including prompt engineering and RAG architectures.
• Perform model development tasks including data preprocessing, feature engineering, model training, and evaluation.
• Optimize model performance, scalability, and cost-efficiency in production environments.
• Implement monitoring, logging, and observability for AI systems.
• Collaborate with cross-functional teams to integrate AI solutions.
• Follow secure development practices (Key Vault, managed identities, RBAC).

Skills

Python

SQL

LLMs

Prompt engineering

RAG architectures

Embeddings / vector search

Transformers

PySpark

Azure

CI/CD

ML frameworks

Tools

Docker

Azure DevOps

GitHub Actions

Azure Databricks

Job description

Ecolab is a global leader in water, hygiene, and energy technologies, dedicated to delivering innovative solutions that make a positive impact worldwide. With operations spanning across 170 countries, Ecolab is committed to sustainability, innovation, and fostering a diverse and inclusive workplace.

There are over 500 of us in our Krakow business center, where we highly specialize in finance, supply chain, accounting, controlling and regulatory. We’re always looking for new talent to join our team. When you come to work at Ecolab, you get to take on some of the world’s most meaningful challenges and have the opportunity to learn and grow, shape your career, make an impact and quickly see the importance of your work.

Right now, we are seeking a highly skilled AI Engineer to design, develop, and deploy AI-powered solutions with a focus on agentic AI systems and intelligent automation on Azure cloud infrastructure. The ideal candidate will have hands‑on experience in building AI/ML models, working with LLMs, and deploying scalable AI solutions to production environments.

What You will Do:

• Design and develop AI-powered applications and agent-based systems for intelligent automation and decision-making
• Build and deploy AI/ML solutions using Azure services (Azure OpenAI, Azure Functions, Azure ML, Cognitive Services, etc.)
• Develop data processing and ML workflows using Azure Databricks and Apache Spark
• Implement and manage CI/CD pipelines using Azure DevOps or GitHub Actions for automated deployment
• Work on LLM-based solutions , including prompt engineering and RAG architectures
• Perform model development tasks including data preprocessing, feature engineering, model training, and evaluation
• Optimize model performance, scalability, and cost-efficiency in production environments
• Implement monitoring, logging, and observability for AI systems
• Collaborate with cross-functional teams (data engineering, product, business stakeholders) to integrate AI solutions
• Follow secure development practices (Key Vault, managed identities, RBAC)

What will You Need:

Required Skills & Qualifications

Technical Expertise

• 2–5 years of experience in AI/ML engineering or data science
• Strong programming skills in Python and SQL
• Experience with Azure cloud services (Azure OpenAI, Azure ML, Functions, Storage, Key Vault)
• Hands‑on experience with Azure Databricks / PySpark for data processing
• Familiarity with CI/CD pipelines (Azure DevOps or GitHub Actions)
• Basic understanding of containerization (Docker)

AI / ML & GenAI Skills

• Strong foundation in Machine Learning and Deep Learning
• Experience with large language models (LLMs) and prompt engineering
• Understanding of: Retrieval-Augmented Generation (RAG)
• Embeddings and vector search
• Transformer-based models
• Exposure to agentic AI concepts / multi-agent workflows
• Experience with ML frameworks: Scikit-learn, TensorFlow, PyTorch, or Transformers

Problem Solving & Engineering Practices

• Strong analytical and problem-solving skills
• Ability to debug and troubleshoot data/ML pipeline issues
• Understanding of software engineering best practices (clean code, version control, code reviews)
• Exposure to testing approaches for AI systems (unit/integration testing)

Preferred Qualifications

• Experience with MLOps tools (MLflow, Azure ML pipelines)
• Knowledge of microservices architecture
• Familiarity with monitoring tools ( Application Insights, Log Analytics )
• Azure certifications (AI Engineer Associate preferred but not mandatory)

What’s In for You:

• Competitive Compensation: Attractive salary and benefits package (lunch subsidy, sport bonus, holiday bonus etc.).
• Work-Life Balance: Flexible working arrangements with hybrid model of work (approx. 50% from the office and 50% from home.
• Matrix Organization: Thrive in our matrix organization, working across Europe with various teams and cultural backgrounds.
• Collaborative Environment: Strong teamwork and diverse interactions.
• Development Opportunities: Personalized plans with rapid progression.
• Versatile Career Paths: Professional growth supported by active committee for different career levels.
• Supportive Culture: High employee satisfaction and responsive feedback.
• Learning and Innovation: Continuous learning and technical training incl. subject matter experts’ trainings, soft skills and LinkedIn learning.
• Social events such as family events and charity auctions.
• Comfortable working environment (Library, relaxation area, casual dress code).
• Parking space for cars and bikes.

At Ecolab, we prioritize our talent‑first philosophy by creating the most capable and diverse team to excel at our nearly three million customer sites. Building on a century of innovation, our 48,000 associates help deliver comprehensive science‑based solutions, data‑driven insights and world‑class service to advance food safety, maintain clean and safe environments, and optimize water and energy use, and improve operational efficiencies and sustainability for customers in the food, healthcare, life sciences, hospitality and industrial markets in more than 170 countries around the world. Our solutions not only enhance operational efficiency but also contribute to sustainability and public health, making a positive impact on the world.

We are committed to eliminating unnecessary complexities and embracing a beginner's mindset, continuously seeking new perspectives and innovative solutions to stay ahead in a rapidly changing world.

We are committed to fair equal and diverse treatment of associates and applicants, furthering the principles of Equal Opportunity Employment.