
SaaS âą Enterprise âą Artificial Intelligence
Gorilla Logic is a company renowned for its expertise in modern software and data engineering. Serving as a strategic partner rather than just a vendor, Gorilla Logic specializes in digital product design, cloud engineering, data and AI delivery, DevOps, quality assurance, and legacy modernization. With a team of skilled digital product designers, solutions architects, and Agile nearshore teams, Gorilla Logic has been instrumental in developing business-critical software applications for Fortune 500 and SMB companies for over 20 years. Their services include creating SaaS platforms, enhancing digital experiences, and providing flexible, security-focused solutions. Gorilla Logic operates with teams located in Costa Rica, Colombia, Mexico, and the United States, emphasizing collaborative partnerships to deliver cutting-edge digital engineering solutions.
Yesterday

SaaS âą Enterprise âą Artificial Intelligence
Gorilla Logic is a company renowned for its expertise in modern software and data engineering. Serving as a strategic partner rather than just a vendor, Gorilla Logic specializes in digital product design, cloud engineering, data and AI delivery, DevOps, quality assurance, and legacy modernization. With a team of skilled digital product designers, solutions architects, and Agile nearshore teams, Gorilla Logic has been instrumental in developing business-critical software applications for Fortune 500 and SMB companies for over 20 years. Their services include creating SaaS platforms, enhancing digital experiences, and providing flexible, security-focused solutions. Gorilla Logic operates with teams located in Costa Rica, Colombia, Mexico, and the United States, emphasizing collaborative partnerships to deliver cutting-edge digital engineering solutions.
âą Design, develop, and deploy large-scale machine learning models and pipelines for production environments. âą Conduct research, experimentation, and tuning to optimize model accuracy, performance, and scalability. âą Build and maintain distributed training and inference systems using frameworks such as Apache Spark or Ray. âą Collaborate with data engineers, backend developers, and product teams to integrate ML components into real-world applications. âą Monitor and improve model performance after deployment, ensuring reliability and stability. âą Document best practices, experiment results, and reproducible methodologies. âą Stay current with new tools, frameworks, and techniques in ML, AI, and distributed systems.
âą 6+ years of experience researching, training, tuning, and launching machine learning models at scale. âą Strong programming skills in Python. âą Experience with distributed frameworks such as Apache Spark or Ray. âą Proficiency with machine learning libraries and frameworks including scikit-learn, pandas, NumPy, XGBoost, and PyTorch. âą Proven experience deploying and maintaining models in production. âą Strong understanding of data pipelines, feature engineering, and model evaluation techniques. âą Experience with version control tools like Git and modern development workflows. âą Excellent analytical, problem-solving, and communication skills.
âą Competitive compensation and benefits package âą Remote-friendly work environment with flexible schedules âą Opportunities to work on impactful AI initiatives using state-of-the-art technology âą Continuous learning and career development support
Apply NowNovember 14
Senior ML Engineer designing and deploying production-grade machine learning solutions for Provectus. Responsible for complex ML problems, mentoring engineers, and building best practices.
AWS
Cloud
Docker
ETL
Numpy
Pandas
Python
PyTorch
Spark
SQL
Tensorflow
Terraform