Senior Machine Learning Engineer

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Gorilla Logic

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SaaS • Enterprise • 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.

501 - 1000 employees

☁️ SaaS

🏢 Enterprise

🤖 Artificial Intelligence

📋 Description

• Design, develop, and deploy large-scale machine learning models and pipelines for production environments. • Conduct research, experimentation, and tuning to optimize model accuracy, performance, and scalability. • Build and maintain distributed training and inference systems using frameworks such as Apache Spark or Ray. • Collaborate with data engineers, backend developers, and product teams to integrate ML components into real-world applications. • Monitor and improve model performance after deployment, ensuring reliability and stability. • Document best practices, experiment results, and reproducible methodologies. • Stay current with new tools, frameworks, and techniques in ML, AI, and distributed systems.

🎯 Requirements

• 6+ years of experience researching, training, tuning, and launching machine learning models at scale. • Strong programming skills in Python. • Experience with distributed frameworks such as Apache Spark or Ray. • Proficiency with machine learning libraries and frameworks including scikit-learn, pandas, NumPy, XGBoost, and PyTorch. • Proven experience deploying and maintaining models in production. • Strong understanding of data pipelines, feature engineering, and model evaluation techniques. • Experience with version control tools like Git and modern development workflows. • Excellent analytical, problem-solving, and communication skills.

🏖️ Benefits

• Competitive compensation and benefits package • Remote-friendly work environment with flexible schedules • Opportunities to work on impactful AI initiatives using state-of-the-art technology • Continuous learning and career development support