Remote Senior ML Engineer at Greenscreens.ai

Join Greenscreens.ai as an ML Engineer, where you will significantly contribute to enhancing logistics technology by designing and fine-tuning ML models to tackle emerging business challenges. Your primary duty will be to ensure the precision and efficiency of our operational models, elevate their performance and streamline ML pipelines. You’ll be tasked with creating and overseeing the infrastructure necessary for model training, performing research, and translating insights directly into improvements for client solutions. Moreover, you will refine our predictive models, assess new features to enhance predictions, and embed intricate business logic into our workflows. Your impact will be vital in steering the evolution of our ML-driven offerings and fostering innovation in the logistics sector.

Key Duties

• Investigate and devise new business features to boost prediction accuracy.
• Improve the Rate Engine through algorithm adjustments, feature trials, and analytic research to enhance data filtering and the quality of predictive models.
• Oversee and sustain active ML models, ensuring both accuracy and operational efficiency.
• Streamline and automate ML pipelines, managing the complete model lifecycle.
• Develop advanced business logic in Python to integrate models within company operations.
• Scale and enhance the performance of existing models (RPS, memory usage).
• Your primary focus will be on tabular datasets.

Qualifications

• A minimum of 3 years in a role as a Data Scientist, ML Engineer, or analogous position.
• Proficiency in Python, SQL, and Git.
• Experience with neural networks, time series analysis, gradient boosting, and random forest techniques.
• Strong foundation in linear algebra, probability, statistics, and optimization.
• Good command of English and Russian for productive team interactions.
• Advanced language skills in both Russian and English are mandatory.

Preferred Technical Skills

• Knowledge of unit testing practices.
• Experience with AWS S3, Docker, and Kubernetes.
• Familiarity with logistics industry applications.
• Active involvement with industry literature and scholarly research.
• Participation in data science competitions (such as Kaggle).
• Experience with hyperparameter tuning techniques.
• Skills in anomaly detection.

Educational Background

• Bachelor's or Master’s degree in Computer Science, Engineering, Mathematics, or a similar discipline.

Perks

Remote Opportunities: Work from anywhere globally, or opt for our office in Vilnius, with specific restrictions on working from Russia and Belarus.

Equity Program: Engage in our options program that allows you to share in the growth and achievements of our startup.

Annual Private Health Insurance Allowance:

Paid Time Off: Enjoy up to four weeks of fully compensated leave each year.