Prepare and validate structured datasets for machine learning tasks, including cleaning, transformation, encoding, scaling, and missing-value handling;
Conduct exploratory data analysis to identify patterns, data quality issues, and opportunities for modeling;
Build, test, and compare ML models for tasks such as regression, classification, clustering, dimensionality reduction, and anomaly detection;
Develop and select features with guidance from senior engineers;
Run experiments, tune model parameters, and evaluate results using appropriate validation approaches and metrics;
Help maintain reproducible ML pipelines, notebooks, experiment tracking, and technical documentation;
Write and maintain automated tests for data and model-related code;
Support the delivery of models through REST APIs or batch-processing workflows;
Document model assumptions, results, limitations, and technical decisions;
Work closely with senior engineers, incorporate feedback, and gradually take ownership of more complex tasks;
Our requirements
1+ year of hands-on Python development experience, including experience with pandas, NumPy, scikit-learn, and Jupyter;
A strong foundation in statistics, probability, and linear algebra, plus exploratory data analysis skills;
An understanding of supervised and unsupervised learning, and practical experience with regression, classification, clustering, dimensionality reduction, and anomaly detection;
Experience preparing structured datasets, including cleaning, transformation, encoding, scaling, and missing-value handling, plus practical feature engineering and feature-selection skills;
An understanding of train/validation/test splits, cross-validation, data leakage, overfitting, and regularization; the ability to select appropriate evaluation metrics, compare models, and perform error analysis;
Familiarity with hyperparameter tuning and reproducible ML pipelines;
SQL skills for data extraction and analysis;
The ability to expose models through REST APIs or batch-processing workflows;
Familiarity with Git, automated testing, Docker, and basic model monitoring;
The ability to explain model behavior, assumptions, limitations, and results;
English at B2 level or higher;
Optional
XGBoost, time-series analysis, recommendation systems, MLflow, model interpretability, cloud services, production ML monitoring, and GenAI, LLM, RAG, prompt-engineering, or agent-development experience;
What we offer
Resources and opportunities for self-education in technical and non-technical areas;
Access to internal conferences and meetups for knowledge sharing and learning from industry experts;
Medical insurance;
Sports activities to promote a healthy lifestyle;
Flexible work options, including remote and hybrid opportunities;
... technical documentation., Collaborate with cross-functional teams in an international environment. Minimum 4 years of commercial experience as a Developer or AI Engineer., Strong proficiency in Python., Practical experience working with LLMs and Generative AI., Hands-on experience with LangChain and LangGraph., Solid understanding ...
Your responsibilities - As a AI/Machine Learning Engineer, you will design and develop predictive and recommendation models, experiment with state-of-the-art ML/AI techniques (including deep learning), and evaluate their impact on business KPIs. You’ll optimize data pipelines and model code using PySpark, Pandas, and MLflow, ...
... a network of outstanding global companies. About the Team and Role This is a foundational hire on ML/AI direction at Solidgate — you'll be one of the first engineers building the function from the ground up, working closely with the ML team to shape it.You'll help stand up the ML/AI direction from scratch — on top of 20M+ ...
Senior AI/ML Engineer Miejsce pracy: Kraków Technologies we use Expected - Python Optional - AWS - https://jobeax.com/link/JSd7UYCSg572jJDY - JavaScript About the project We are looking for a Senior AI/ML Engineer with strong hands-on experience building and deploying AI solutions in real-world products. This role requires ...
... protection – into every agent workflow, including any automated output that reaches an external party Master’s degree in computer science, Machine Learning, Data Engineering or a related field, 5+ years of overall software/ML engineering experience and 2+ hands-on GenAI/LLM/agentic experience, Strong, hands-on experience with ...
... multilingual documents and forms - Supporting new AI-driven automation initiatives emerging in the project pipeline Requirements: - Strong experience in Data Engineering - Hands-on expertise with Azure Databricks - Experience with Azure Synapse Analytics - Very good knowledge of Azure Cloud services - Experience working with ...
... practices. The role works across Data Engineering, Product, Risk and Commercial teams to turn business problems into measurable AI solutions. Strong production ML experience, Python, Spark/PySpark, SQL and ML lifecycle expertise are central to the position. Day to day that means the Senior AI/ML Engineer – Applied AI Lead ...
Operating system, Windows About the project, We are looking for an experienced AI Engineer who will be responsible for designing, deploying, and maintaining AI/ML solutions in production environments. The role combines expertise in Machine Learning Engineering, MLOps, and basic administration and optimization of GPU infrastructure ...
... more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. - 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data ...
... oparte na sztucznej inteligencji, LLM i analizie danych. Rola obejmuje zarówno tworzenie nowych rozwiązań, jak i rozwój oraz utrzymanie istniejących komponentów AI/ML., , Kluczowe technologie, Python, AI, Machine Learning, LLM, RAG, NLP, Agentic AI, TensorFlow, PyTorch, Prompt Engineering, Generative AI, Cloud, , Tryb pracy: ...
... wymaganiami regulacyjnymi. Osoba na tym stanowisku będzie współpracować z zespołami Data Engineering, Data Science i AI Governance, wykorzystując platformy takie jak MLflow, Databricks czy Azure ML. Twój zakres obowiązków - Wdrażanie mechanizmów AI Governance w cyklu życia modeli ML, w tym Model Registry, procesów zatwierdzania ...