DOIT Software

We are currently looking for a Machine Learning Engineer to join a technology company specializing in navigation hardware for aerial vehicles. This is a fully remote position.

The company fosters a fast-paced startup culture with direct communication, a flat hierarchy, and minimal bureaucracy. You will work with people who value the Growth Mindset, embrace challenges, aren’t afraid to learn from mistakes, and focus on finding solutions rather than pointing fingers.

The company actively integrates automation and AI technologies into all company processes to be 10x more efficient, reduce routines, and free up time for creative jobs.

Key responsibilities:

• Perform data analysis to evaluate data quality, identify trends, and ensure suitability for machine learning experiments.
• Prepare and preprocess datasets, ensuring best practices for model generalization and robustness in ML models.
• Prototype and optimize data processing pipelines, collaborating with the DevOps team for seamless deployment.
• Design, train, and evaluate ML models in collaboration with senior engineers.
• Analyze experiment results, identify potential pitfalls, and propose improvements for model performance.

• Proactively communicate key findings, intermediate analyses, and experiment results to stakeholders and partners, translating insights into actionable recommendations.

   

Required skills:

• Upper-intermediate, preferably Advanced English.
• Master’s or PhD degree in Computer Science, Machine Learning, Robotics, or a related field.
• Commercial experience in Machine Learning, Robotics, or a related field.
• Solid command of Machine Learning, Statistics, and Signal Analysis.
• Hands-on experience with Python and ML frameworks such as TensorFlow or PyTorch, SciPy, and Scikit-learn.
• Strong understanding of data preprocessing, feature engineering, and model evaluation.
• Familiarity with supervised and unsupervised learning techniques applied to sensor or image data.

• Basic understanding of software engineering principles, including version control (Git) and containerization (Docker).

   

Preferred qualifications:

• Command of at least one other language for data analysis, such as R and Scala.
• Familiarity with the Spark data analysis framework.
• Exposure to robotics, reinforcement learning, SLAM (Simultaneous Localization and Mapping), or sensor fusion.
• Experience working with real-time sensor data (e.g., LiDAR, camera, IMU).

• Understanding of cloud-based ML model deployment and optimization techniques.

   

Note! When possible, add a link to your GitHub and any code examples with your application.

We are currently looking for a Machine Learning Engineer to join a technology company specializing in navigation hardware for aerial vehicles. This is a fully remote position.

The company fosters a fast-paced startup culture with direct communication, a flat hierarchy, and minimal bureaucracy. You will work with people who value the Growth Mindset, embrace challenges, aren’t afraid to learn from mistakes, and focus on finding solutions rather than pointing fingers.

The company actively integrates automation and AI technologies into all company processes to be 10x more efficient, reduce routines, and free up time for creative jobs.

Key responsibilities:

• Perform data analysis to evaluate data quality, identify trends, and ensure suitability for machine learning experiments.
• Prepare and preprocess datasets, ensuring best practices for model generalization and robustness in ML models.
• Prototype and optimize data processing pipelines, collaborating with the DevOps team for seamless deployment.
• Design, train, and evaluate ML models in collaboration with senior engineers.
• Analyze experiment results, identify potential pitfalls, and propose improvements for model performance.

• Proactively communicate key findings, intermediate analyses, and experiment results to stakeholders and partners, translating insights into actionable recommendations.

   

Required skills:

• Upper-intermediate, preferably Advanced English.
• Master’s or PhD degree in Computer Science, Machine Learning, Robotics, or a related field.
• Commercial experience in Machine Learning, Robotics, or a related field.
• Solid command of Machine Learning, Statistics, and Signal Analysis.
• Hands-on experience with Python and ML frameworks such as TensorFlow or PyTorch, SciPy, and Scikit-learn.
• Strong understanding of data preprocessing, feature engineering, and model evaluation.
• Familiarity with supervised and unsupervised learning techniques applied to sensor or image data.

• Basic understanding of software engineering principles, including version control (Git) and containerization (Docker).

   

Preferred qualifications:

• Command of at least one other language for data analysis, such as R and Scala.
• Familiarity with the Spark data analysis framework.
• Exposure to robotics, reinforcement learning, SLAM (Simultaneous Localization and Mapping), or sensor fusion.
• Experience working with real-time sensor data (e.g., LiDAR, camera, IMU).

• Understanding of cloud-based ML model deployment and optimization techniques.

   

Note! When possible, add a link to your GitHub and any code examples with your application.

We are currently looking for a Machine Learning Engineer to join a technology company specializing in navigation hardware for aerial vehicles. This is a fully remote position.

The company fosters a fast-paced startup culture with direct communication, a flat hierarchy, and minimal bureaucracy. You will work with people who value the Growth Mindset, embrace challenges, aren’t afraid to learn from mistakes, and focus on finding solutions rather than pointing fingers.

The company actively integrates automation and AI technologies into all company processes to be 10x more efficient, reduce routines, and free up time for creative jobs.

Key responsibilities:

• Perform data analysis to evaluate data quality, identify trends, and ensure suitability for machine learning experiments.
• Prepare and preprocess datasets, ensuring best practices for model generalization and robustness in ML models.
• Prototype and optimize data processing pipelines, collaborating with the DevOps team for seamless deployment.
• Design, train, and evaluate ML models in collaboration with senior engineers.
• Analyze experiment results, identify potential pitfalls, and propose improvements for model performance.

• Proactively communicate key findings, intermediate analyses, and experiment results to stakeholders and partners, translating insights into actionable recommendations.

   

Required skills:

• Upper-intermediate, preferably Advanced English.
• Master’s or PhD degree in Computer Science, Machine Learning, Robotics, or a related field.
• Commercial experience in Machine Learning, Robotics, or a related field.
• Solid command of Machine Learning, Statistics, and Signal Analysis.
• Hands-on experience with Python and ML frameworks such as TensorFlow or PyTorch, SciPy, and Scikit-learn.
• Strong understanding of data preprocessing, feature engineering, and model evaluation.
• Familiarity with supervised and unsupervised learning techniques applied to sensor or image data.

• Basic understanding of software engineering principles, including version control (Git) and containerization (Docker).

   

Preferred qualifications:

• Command of at least one other language for data analysis, such as R and Scala.
• Familiarity with the Spark data analysis framework.
• Exposure to robotics, reinforcement learning, SLAM (Simultaneous Localization and Mapping), or sensor fusion.
• Experience working with real-time sensor data (e.g., LiDAR, camera, IMU).

• Understanding of cloud-based ML model deployment and optimization techniques.

   

Note! When possible, add a link to your GitHub and any code examples with your application.

We are currently looking for a Machine Learning Engineer to join a technology company specializing in navigation hardware for aerial vehicles. This is a fully remote position.

The company fosters a fast-paced startup culture with direct communication, a flat hierarchy, and minimal bureaucracy. You will work with people who value the Growth Mindset, embrace challenges, aren’t afraid to learn from mistakes, and focus on finding solutions rather than pointing fingers.

The company actively integrates automation and AI technologies into all company processes to be 10x more efficient, reduce routines, and free up time for creative jobs.

Key responsibilities:

• Perform data analysis to evaluate data quality, identify trends, and ensure suitability for machine learning experiments.
• Prepare and preprocess datasets, ensuring best practices for model generalization and robustness in ML models.
• Prototype and optimize data processing pipelines, collaborating with the DevOps team for seamless deployment.
• Design, train, and evaluate ML models in collaboration with senior engineers.
• Analyze experiment results, identify potential pitfalls, and propose improvements for model performance.

• Proactively communicate key findings, intermediate analyses, and experiment results to stakeholders and partners, translating insights into actionable recommendations.

   

Required skills:

• Upper-intermediate, preferably Advanced English.
• Master’s or PhD degree in Computer Science, Machine Learning, Robotics, or a related field.
• Commercial experience in Machine Learning, Robotics, or a related field.
• Solid command of Machine Learning, Statistics, and Signal Analysis.
• Hands-on experience with Python and ML frameworks such as TensorFlow or PyTorch, SciPy, and Scikit-learn.
• Strong understanding of data preprocessing, feature engineering, and model evaluation.
• Familiarity with supervised and unsupervised learning techniques applied to sensor or image data.

• Basic understanding of software engineering principles, including version control (Git) and containerization (Docker).

   

Preferred qualifications:

• Command of at least one other language for data analysis, such as R and Scala.
• Familiarity with the Spark data analysis framework.
• Exposure to robotics, reinforcement learning, SLAM (Simultaneous Localization and Mapping), or sensor fusion.
• Experience working with real-time sensor data (e.g., LiDAR, camera, IMU).

• Understanding of cloud-based ML model deployment and optimization techniques.

   

Note! When possible, add a link to your GitHub and any code examples with your application.

We are currently looking for a Senior Python Developer to join a project with one of our clients from Norway. 

Product/client: AI-driven construction management solution that helps to streamline data access, automate evaluations, and connect critical project information.

Open position details: As a Senior Python Developer, you’ll be instrumental in designing, developing, and deploying the backend systems and AI infrastructure that power the client's solutions. You will work closely with the CTO and cross-functional product team to bring their ambitious roadmap to life, contributing to both product and technical strategy.

Requirements:
 

• Proven experience within Python development, ideally within a data-driven or AI-focused environment;
• Strong coding skills, with proficiency in Python and relevant frameworks (FastAPI);
• Experience with natural language processing (NLP) techniques;
• Experience with Knowledge Graph systems and RAG pipelines is required;
• Familiar with cloud platforms (Azure) and their services;
• Experience in writing robust unit and integration tests.

Key Responsibilities:

• Design and Develop Scalable Python Code:
  Write modular, efficient, and maintainable Python code following best practices and internal standards. Ensure long-term scalability and ease of collaboration.
• Build and Optimize RAG Pipelines:
  Design, develop, and maintain advanced Retrieval-Augmented Generation (RAG) pipelines capable of efficiently processing large-scale unstructured textual data, ensuring high performance and reliability.
• Implement and Enhance Knowledge Graph Systems:
  Take a leading role in the development and refinement of knowledge graph components to organize and relate project-critical data for advanced querying and reasoning.
• Architect Robust Software Solutions:
  Participate actively in architectural discussions and decision-making, contributing your expertise to building scalable backend architectures and AI workflows that are resilient and future-proof.
• Ensure Code Quality and Reliability:
  Proactively apply rigorous testing methods—including unit, integration, and performance tests—to maintain high standards of software reliability, speed, and accuracy.
• Collaborate Cross-Functionally:
  Engage actively in code reviews, pair programming, and knowledge-sharing sessions, promoting a collaborative and positive engineering culture.
• Stay Ahead with Emerging Technologies:
  Continuously explore new methodologies, frameworks, and advancements in Python, NLP, RAG, Knowledge Graphs, and other relevant fields to drive innovation and efficiency improvements within our platform.

Longevity of project: long-term. 
 

Start date: ASAP.