Ml Engineer

TL;DR

Ml Engineer (AI Engineering): Developing intelligent machine learning models and scalable ML pipelines with an accent on model deployment, performance optimization, and reproducibility. Focus on designing, training, and evaluating diverse ML models including NLP and deep learning, and integrating them into production environments.

Location: Hybrid in Warsaw with option for full remote or office work

Company

hirify.global is a pre-IPO global software development company with over 18 years of experience delivering full-cycle IT services across multiple industries worldwide.

What you will do

• Design, train, and evaluate machine learning models including supervised, unsupervised, and NLP approaches.
• Build scalable data and ML pipelines using modern tools and cloud services.
• Collaborate with experts to prepare training datasets and ensure data quality.
• Deploy ML models for batch or real-time inference and monitor their performance.
• Optimize models for performance, interpretability, and cost efficiency.
• Document ML workflows to ensure reproducibility and maintainability.

Requirements

• Minimum 3 years experience as a Machine Learning Engineer or similar role.
• Proficiency in Python and ML libraries such as scikit-learn, pandas, NumPy, and matplotlib.
• Experience with deep learning frameworks like TensorFlow, PyTorch, or Keras.
• Hands-on experience deploying ML models using AWS SageMaker and familiarity with AWS Bedrock for foundation and generative models.
• Knowledge of SQL and experience with structured and semi-structured data.
• English level: Intermediate+ or higher.

Nice to have

• Experience with cloud platforms (AWS, GCP, Azure) and managed ML services.
• Familiarity with ML lifecycle tools such as MLFlow, DVC, Airflow.
• Understanding of CI/CD for ML systems and big data tools like Spark or Hadoop.
• Knowledge of data security and ethical AI considerations.
• Experience with NLP including LLMs, computer vision, or agentic AI.

Culture & Benefits

• Work with leaders in FinTech, Healthcare, Retail, Telecom, and other industries.
• Flexible work conditions: fully remote, office, or hybrid options.
• Professional, financial, and career growth with mentoring and adaptation systems.
• Access to corporate training portal and certification compensation.
• Private health insurance, sports activity compensation, and English courses.
• Engaging corporate life with events, referral programs, and bonuses.