Machine Learning Engineer

Machine Learning Engineer – Contract/Freelance – Remote - $7000 USD per monthFully Remote from anywhere in South America12 month contract$7000 USD per monthResponsibilitiesPartner with product and engineering stakeholders to define the AI/ML roadmap aligned with business goals.Design, prototype, and deploy production-ready ML models, with a focus on computer vision and multimodal understanding in the video domain.Apply both generative and discriminative machine learning techniques to real-world problems in the video content spaceWork on task types including text-to-image generation, image segmentation, and object and pose detection — with opportunities to leverage and deploy public-domain models for speech recognition and audio intelligence.Own the full ML lifecycle, from data acquisition and preprocessing to training, evaluation, and deploymentDesign and implement efficient, lightweight ML models optimized for deployment on mobile and edge devices.Collaborate with engineering teams to integrate ML models into the partner’s platformDevelop LLM-based Agent functionality with custom tools and workflowsOptimize models for real-time inference and performance on mobile device and cloud platformsConduct code reviews, promote engineering best practices, and mentor junior team membersStay up-to-date with the latest research, tools, and industry trends in AI/ML and assess their relevance for our growth partner’s productExperience & QualificationsExperience in applied machine learning, with a strong track record of building and deploying models in productionProficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)Experience with both generative (e.g., diffusion, transformer-based) and discriminative (e.g., classification, segmentation) AI approachesStrong understanding of data pipelines, model evaluation, and feature engineeringExperience with computer vision and/or audio processing techniques is a strong advantageFamiliarity with deploying ML models on cloud platforms (e.g., GCP, AWS) and edge/mobile environments (e.g., ONNX, TensorFlow Lite)Advanced English