Machine Learning Engineer

NTIATIVE IT Recruitment; Warszawa; On-site; PLN 180,000 - 240,000; Full time

Job summary

NTIATIVE IT Recruitment is seeking a hands-on Member of Technical Staff, Machine Learning to build core ML systems powering our AI products.

You will work across the full ML lifecycle—from data prep to deployment—in production environments alongside senior ML engineers and product teams to deliver scalable, reliable AI features.

Qualifications

• Strong foundation in machine learning and modern neural network architectures.
• Hands-on experience training, fine-tuning, or deploying machine learning models.
• Strong proficiency in Python.
• Experience with PyTorch and/or JAX.
• Familiarity with GPU-based model training and inference.
• Ability to write clean, production-quality code.
• Strong problem-solving skills and the ability to learn new tools and technologies quickly.
• Curious, coachable, and eager to learn from real-world production systems.

Responsibilities

• Build, improve, and maintain core machine learning components used in production.
• Contribute across the ML lifecycle, including data preparation, training, evaluation, inference, and deployment.
• Fine-tune and adapt machine learning models as part of larger production systems.
• Design and implement evaluation frameworks and testing to better understand model performance and behavior.
• Build and maintain data pipelines supporting both real-world and synthetic datasets.
• Monitor, debug, and improve model performance using production signals and user feedback.
• Investigate and resolve production issues across ML systems, pipelines, and infrastructure.
• Collaborate closely with senior ML engineers, researchers, and product teams to deliver impactful AI features.
• Develop solutions that meet production requirements for scalability, latency, reliability, safety, and cost efficiency.

Skills

Machine learning

Python

Problem solving

Learning fast

Curiosity

Tools

PyTorch

JAX

GPU training

Production code

Job description

We are looking for a Member of Technical Staff, Machine Learning to help build the core machine learning systems powering our AI products. This is a hands-on engineering role where you'll work on production systems from day one, gaining firsthand experience with how large-scale ML operates beyond research environments.

You’ll contribute across the full ML lifecycle, from data preparation and model training to evaluation, deployment, and continuous improvement. Working alongside experienced ML engineers, researchers, and product teams, you’ll help transform cutting-edge ideas into reliable, scalable production systems while developing strong engineering and systems expertise.

Responsibilities

• Build, improve, and maintain core machine learning components used in production.
• Contribute across the ML lifecycle, including data preparation, training, evaluation, inference, and deployment.
• Fine-tune and adapt machine learning models as part of larger production systems.
• Design and implement evaluation frameworks and testing to better understand model performance and behavior.
• Build and maintain data pipelines supporting both real-world and synthetic datasets.
• Monitor, debug, and improve model performance using production signals and user feedback.
• Investigate and resolve production issues across ML systems, pipelines, and infrastructure.
• Collaborate closely with senior ML engineers, researchers, and product teams to deliver impactful AI features.
• Develop solutions that meet production requirements for scalability, latency, reliability, safety, and cost efficiency.

Requirements

• Strong foundation in machine learning and modern neural network architectures.
• Hands-on experience training, fine-tuning, or deploying machine learning models.
• Strong proficiency in Python.
• Experience with PyTorch and/or JAX.
• Familiarity with GPU-based model training and inference.
• Ability to write clean, maintainable, production-quality code.
• Strong problem-solving skills and the ability to learn new tools and technologies quickly.
• Curious, coachable, and eager to learn from real-world production systems.

Nice to Have

• Experience working with production ML systems.
• Experience building or maintaining data pipelines.
• Familiarity with model evaluation, monitoring, and observability.
• Experience with distributed training or large-scale AI infrastructure.

Why Join Us?

We believe the world's best products are built by small, exceptionally talented teams. We maintain a high-talent-density culture where ownership, collaboration, and execution matter. We move quickly, balancing speed with quality while continuously learning and improving.

Joining our team means working on challenging AI problems, learning from experienced engineers, and contributing to products that deliver meaningful impact to users around the world.