Machine Learning Engineer

Technosylva is a leading SaaS company specializing in operational support and risk analytics solutions for wildfires and extreme weather events. Our mission is to reduce the impact of these events by delivering proactive, actionable intelligence that enables better decision-making.

We offer a suite of software solutions specifically designed to mitigate risks associated with both wildfires and extreme weather conditions. These solutions are used by some of the largest investor-owned utilities (IOUs), fire management agencies, and other key organizations across the United States.

Our products help anticipate risk, generate on-demand wildfire spread predictions, and support infrastructure hardening analysis—while also aiding regulatory compliance and reporting processes. Although initially developed for utilities and government agencies, our solutions are rapidly gaining traction in other sectors, such as transmission operators, insurance companies, and emerging industries increasingly exposed to climate risk.

Founded in 1997, Technosylva has been delivering mission-critical solutions for over two decades. In recent years, the company has undergone a transformation and period of rapid growth, now boasting a team of over 180 employees and an international presence in more than 10 countries.

JOB DESCRIPTION

We are seeking an expert to design, build, and automate predictive analytics systems that forecast weather variables using satellite data and numerical weather prediction (NWP) model outputs as predictors. The ideal candidate will collaborate with atmospheric scientists to develop machine learning (ML) platforms that generate short- and long-term weather forecasts for specific locations, regions, and grids using complex 4D datasets. This position will report directly to the principal scientist.

RESPONSIBILITIES

• Create machine learning models that predict weather variables, including extreme weather events, using sparse data.
• Choose the most suitable machine learning algorithms based on the specific characteristics and requirements of the dataset.
• Work closely with atmospheric scientists to understand weather patterns and integrate their expertise into the development of accurate forecasts.
• Accelerate and automate the training and testing processes of ML models on GPU-based systems for faster, more efficient performance.
• Handle and analyze complex, multi-dimensional weather data from satellite and numerical weather prediction models.
• Design and implement platforms that generate weather forecasts for specific locations, regions, and grids.
• Contribute to the development of long-term ML design strategies and technology frameworks for the company’s growth.
• Optimize ML models for scalability and performance, particularly when processing large datasets on high-performance computing systems.
• Support the data engineer with various data storage design and implementation projects.
• Assist in the development of future ML programs that support the mission-critical tasks of the company and clients.

REQUIRED SKILLS

• Expertise in statistical models and numerical methods for forecasting weather data and extreme events.
• Ability to create, automate, and interpret diagnostic tools for model validation and performance evaluation.
• Ability to design and implement solutions that predict extreme events, particularly those trained on sparse data.
• Operating Systems : Proficiency with Linux (Ubuntu), including experience optimizing Linux desktops and servers.
• Programming Languages :

Python 3.x with libraries such as Numpy, Pandas, Xarray, and Dask for data manipulation and analysis.

• Machine Learning Algorithms & Frameworks :

Experience with algorithms such as Self-Organizing Maps, Ensemble Learning (e.g., Random Forest), Support Vector Machines (SVM), and Artificial Neural Networks (ANN).

• Familiarity with Scikit-learn, XGBoost, and RAPIDS for machine learning model development and optimization.
• Databases : Experience with relational databases such as PostgreSQL / PostGIS and / or MySQL / MariaDB for storing and managing large datasets.
• Container Technologies : Familiarity with Docker for creating and managing containers for ML and data processing tasks.
• Fluency in English is required (C1).

PREFERRED SKILLS

• Programming languages :

Python 3.x.

• Hardware :

GPU systems, high-performance Computing Clusters.

BENEFITS

• Competitive annual salary.
• Annual bonus based on individual and company performance.
• Remote work options available.

DISCLAIMERFinal compensation and benefits will depend on a variety of factors including location, experience, training, qualifications, and market demand.

COMMITMENT TO INCLUSIONTechnosylva is an equal opportunity employer. We are committed to fostering an inclusive environment where diverse perspectives lead to better solutions.

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