AI Energy Technologies Machine Learning Engineer @

2 weeks ago

Remote, Czech Republic BONEFFICE SYSTEM SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ Full time
Required Skills and Qualifications
  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field. 
  • 3+ years of professional experience in Python development and machine learning. 
  • Proficient in using Python and data science libraries such as sklearn, Keras, PyTorch, pandas, and numpy. 
  • Strong experience in data analysis, wrangling, and preprocessing techniques. 
  • Hands-on experience with CI/CD tools (Docker, Portainer) and NoSQL databases. 
  • Prompt engineering knowledge and hands on experience with LLMs 
  • Solid understanding of software engineering principles and version control using GIT. 
  • Ability to create dashboards for data visualization (Dash or React) 
  • Excellent problem-solving skills and the ability to work on complex issues requiring in-depth evaluation of variable factors. 
  • Proficiency in English (B2+/C1 level) with strong verbal and written communication skills. 
  • Ability to work independently in a fully remote environment, with a high level of discipline. 
Desirable Additional Skills
  • Degree in Computer Science, Data Science, Power Engineering, or related field. 
  • Experience in projects related to the industry or energy sector, particularly with virtual twins and predictive maintenance. 
  • Knowledge of power engineering principles and challenges in the energy sector. 
  • Familiarity with AWS cloud computing platform. 
  • Experience with Jira for project management. 
  • Ability to mentor junior team members and lead technical discussions. 

AI Energy Technologies Machine Learning Engineer

Position Overview

We are looking for a highly skilled and motivated Machine Learning Engineer to join our cutting-edge team. This role combines the core responsibilities of both a Python Developer and a Data Scientist, making it ideal for someone with a strong background in both software development and data science. As a Machine Learning Engineer, you will focus on designing, developing, and deploying machine learning models and data processing pipelines that drive significant innovations in the energy sector. This role requires advanced Python programming skills, expertise in machine learning frameworks, and a deep understanding of data handling and analysis techniques. LLMs and RAG experience is a big plus.

What We Offer

  • The opportunity to work remotely with a flexible schedule. 
  • Competitive salary  
  • A dynamic and supportive work environment with a focus on personal and professional growth. 
  • The chance to work on projects that have a real-world impact on energy sustainability and efficiency. 
  • Access to the latest tools, technologies, and training to help you succeed. 
,[Model Development and Implementation: , Design, develop, and deploy machine learning and deep learning models tailored to the energy sector, focusing on applications like predictive maintenance and virtual twins. , Implement sophisticated algorithms and data processing pipelines using Python and libraries such as sklearn, Keras, and PyTorch. , Continuously optimize models for performance, scalability, and reliability. , RAG for LLMs deployed on premises , Data Handling and Analysis: , Lead data analysis, wrangling, and preprocessing activities to prepare high-quality datasets for machine learning and deep learning models. , Work with NoSQL databases and data engineering tools to manage and manipulate large-scale datasets efficiently. , Apply power engineering knowledge to address specific industry challenges through data-driven solutions. , Software Development: , Develop and maintain robust Python applications focusing on backend services and data processing workflows. , Utilize CI/CD tools like Docker and Portainer to ensure smooth deployment, scalability, and maintenance of machine learning applications. , Collaborate with cross-functional teams to define software specifications, gather requirements, and develop innovative solutions that meet business needs. , Collaboration and Communication: , Work closely with data scientists, engineers, and other stakeholders to understand business requirements and translate them into technical solutions. , Communicate insights and results effectively to both technical and non-technical audiences. , Continuous Learning and Improvement: , Stay updated with the latest advancements in AI, machine learning, and deep learning technologies. , Continuously improve code quality, system design, and processes. ] Requirements: AI, Machine learning, Python, Data science, Keras, PyTorch, Data analysis, Deep learning, NoSQL, Data engineering, Docker, Degree, pandas, NumPy, Git, Data visualization, React, Communication skills, AWS, Cloud computing, Jira, Project management Additionally: Flat structure, Small teams, International projects.

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