ENTRADA AI SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ
6. 11. 2025
Informacje o stanowisku
technologies-expected :
Machine Learning
Databricks
Python
MLflow
MLOps
technologies-optional :
TensorFlow
Pytorch
scikit-learn
AWS
Azure DevOps
about-project :
Entrada AI, Inc. is seeking an experienced Senior Machine Learning Engineer to join our growing team of consultants. In this role, you will be responsible for designing, developing, and deploying machine learning models and algorithms to solve complex business challenges with Databricks. You will work closely with data scientists, data engineers, and business stakeholders to build scalable and efficient machine learning solutions.
responsibilities :
Design and implement machine learning models and algorithms with Databricks, including predictive analytics, natural language processing, computer vision, and more.
Lead the end-to-end development process, from data collection and preprocessing to model deployment and monitoring.
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Optimize and fine-tune models for performance, accuracy, and scalability in a production environment.
Stay up-to-date with the latest advancements in machine learning and AI, and apply them to improve existing systems.
Mentor and guide junior engineers and data scientists in best practices for machine learning and data engineering.
Contribute to the development of machine learning infrastructure, including data pipelines, model serving frameworks, and monitoring tools.
Collaborate with client stakeholders to drive solutions to solve business problems.
requirements-expected :
Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field; PhD is a plus.
5+ years of experience in machine learning engineering or related fields.
3+ years of experience with Databricks
Proficiency in programming languages such as Python, R, or Java, with a strong understanding of machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Experience with cloud platforms and MLOps tools, such as MLflow, for model deployment and monitoring.
Strong problem-solving skills and ability to work in a fast-paced environment.
Excellent communication and collaboration skills, with a track record of working effectively in cross-functional teams.
