Senior/Lead Machine Learning Engineer

IFS; Kraków; On-site; PLN 191,245 - 276,242; Full time

Job summary

IFS is looking for an ML Engineer in Kraków, Poland, to build and deploy AI-driven solutions while maintaining scalable AI/ML infrastructure. The ideal candidate will have strong Python skills, experience with cloud platforms, and a foundational understanding of AI/ML concepts.

This role involves collaborating with cross-functional teams to create production-ready ML pipelines. A bachelor's or master's degree in a relevant field and at least 3 years of software development experience are required.

Qualifications

• At least 3+ years of experience in software development.
• Strong proficiency in Python and experience with relevant libraries.
• Familiarity with cloud computing platforms and CI/CD practices.

Responsibilities

• Build and deploy AI-driven solutions.
• Maintain scalable AI/ML infrastructure.
• Collaborate with teams on ML pipeline creation.

Skills

Python proficiency

Experience with NumPy and Pandas

Familiarity with Azure

Understanding of AI/ML concepts

Data preprocessing skills

Analytical skills

Strong communication skills

Education

Bachelor's or master's degree in Computer Science, Software Engineering, or Data Science

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Job description

Job Description

An MLengineer at IFS is part software engineer, part dev ops engineer and ML savvy, who combines knowledge of systems and applications, machine learning and artificial intelligence to build and deploy AI-driven solutions. The work is focused on designing and maintaining high-performance, scalable AI/ML infrastructure, building, and executing ML pipelines efficiently, serving models at scale, and creating the tools for continuous monitoring and improvements.

Someone in this role uses their technical know-how to translate high-value and innovative AI opportunities into deployable and sustainable products. ML engineers are well-versed on AI/ML techniques, ranging from statistical learning, computer vision to generative AI. They have strong foundations in software engineering, ML algorithms and mastered several AI/ML serving frameworks. ML engineers work in close collaboration with data scientists, data engineers, architects, and DevOps engineers, on the creation and deployment of highly scalable infrastructure and AI-driven solutions.

ML engineers act as AI infrastructure experts in the development of production-ready, scalable ML pipelines and AI-driven solutions along with our data scientist, data engineers, domain experts, partners, and clients.

In addition, ML engineers at IFS continuously expand their knowledge of AI infrastructure, model monitoring/observability and drift detection, functional and business process domain knowledge and share this knowledge to guide others.

Qualifications

Required Skills:

• Programming Skills: Strong proficiency in Python and experience with relevant libraries (NumPy, Pandas, Kserve, etc.). Knowledge of additional languages like Go, C#, or SQL is a plus.
• Cloud Platforms & Dev Ops: Familiarity with cloud computing platforms (Azure), infrastructure as code (terraform, helm charts), CI/CD, Git Ops with ArgoCD and containerization technologies (Docker, Kubernetes).
• AI/ML Fundamentals: Foundational understanding of machine learning concepts, including supervised and unsupervised learning, deep learning, and model evaluation techniques.
• Data Handling: Proficiency in data preprocessing and feature engineering. Experience with relational and vector databases.
• Analytical Skills: Excellent analytical skills, with the ability to interpret complex datasets and derive actionable insights.
• Communication Skills: Excellent verbal and written communication skills, with the ability to effectively collaborate with cross‑functional teams and stakeholders
• Education and Experience: A bachelor's or master's degree in Computer Science, Software Engineering, Data Science, or a related field, with at least 3+ years of experience in software development, including some experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.

Additional Information

We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships.