TL;DR

Senior Data/ML Engineer (AI): Managing the full lifecycle of machine learning models, from development and deployment to monitoring and optimization, ensuring high performance and reliability. Focus on implementing MLOps practices, building big data processing pipelines using Spark and Python, and exploring cloud-based AI/ML solutions.

Location: Elastic hybrid from Gdynia / Gdańsk / Warszawa / Łódź (at least 2-3 days per week from the office)

Salary: 1080 - 1280 PLN/day on B2B

Company

%hirify_global% is a Polish company with over 700 experienced experts, creating highly specialised teams for clients from all over the world and is a premier partner to a leading financial group in the Nordic countries.

What you will do

Manage the full lifecycle of ML models, including development, deployment, monitoring, and performance optimization.
Implement MLOps practices such as CI/CD, testing, monitoring, and automation of ML workflows.
Build and maintain distributed big data processing pipelines for both structured and unstructured data using Spark and Python.
Enrich and transform corporate data to enable analytics, visualization, and advanced machine learning models.
Collaborate with cross-functional teams, including data scientists, DevOps engineers, and IT, to deliver high-quality ML solutions.
Optimize current MLOps practices and libraries to apply them to a broader range of use cases.

Requirements

Minimum 5 years of experience with Python and Spark.
Hands-on experience with AWS services for ML and data processing covering data ingestion, model training, batch inference, and automation pipelines.
Strong understanding of AWS infrastructure setup and automation using AWS CLI, boto3, and IAM roles to ensure reproducible and secure ML workflows.
Solid knowledge of algorithms, data structures, statistics, and linear algebra.
Experience with ML frameworks (TensorFlow or PyTorch), including training, refining, and deploying models into user-facing applications.
Fluency in English.

Nice to have

Experience designing and implementing ML models (e.g., Propensity, Customer Lifetime Value, Micro-segmentation, channel recommendation models)

Culture & Benefits

Flexible work organization.
International work environment with daily interaction with the English language.
Scandinavian organizational culture providing work-life balance.
Time for additional training (financed).
Regular integration meetings with the Jit community.

Senior Data/Ml Engineer (Ai)