AI Engineer - AI Department

Job Description Benefits:401(k)401(k) matchingCompetitive salaryDental insuranceHealth insuranceOpportunity for advancementPaid time offRelocation bonusVision insuranceWellness resourcesPetlibro | San Jose, CAAbout PetlibroPetlibro is a design-thinking company creating products that nurture the intertwined lives of pets and their people. We launched with a philosophy that good design, in form and in function, can make a difference. Petlibro innovates with the latest technology to solve everyday problems for modern pet parents and revolutionize how we care for our pets.Since 2019, Petlibro has grown into one of the best-selling pet tech brands globally. From smart feeders with app insights to ultra-filtered automatic fountains to pet-health-focused smart apps, our products are engineered to magnify the bond between your pet and you. We are now building AI-powered products and services for modern pet care.Job SummaryWe are looking for an AI Engineer to design, train, and deploy AI models that power intelligent pet care and animal monitoring products. You will work across the full model lifecycle, from data curation and fine-tuning to production serving and on-device deployment. The role spans computer vision, vision-language models (VLMs), large language models (LLMs), and agentic AI systems, with a strong focus on animal behavior understanding and multimodal reasoning.Key ResponsibilitiesFine-tune LLMs and VLMs for pet care and animal behavior domains using modern post-training methods (SFT, DPO, GRPO/DAPO)Develop and evaluate computer vision models for animal detection, pose estimation, activity recognition, and health monitoringBuild multimodal AI pipelines that combine video, audio, weight sensor data, and other sensor modalities for real-time animal behavior analysisDesign and operate model serving infrastructure with high throughput and low latency (vLLM, TensorRT-LLM)Implement RAG systems and agentic workflows for domain-specific knowledge retrieval and automated decision-makingOptimize models for on-device / edge deployment using quantization (GPTQ, AWQ, INT4/INT8), distillation, etc.Curate and manage training datasets including synthetic data generation and annotation pipelines for animal imagery and videoDevelop evaluation frameworks and benchmarks specific to animal AI tasks (behavior classification accuracy, false alert rates, etc.)Collaborate with firmware and embedded engineers to ship models on resource-constrained hardwareMonitor model performance in production, set up drift detection, and maintain model versioning and rollback processesQualifications & SkillsBachelor's or Master's degree in Computer Science, AI/ML, Electrical Engineering, or a related field2+ years of hands-on experience training and deploying ML models in productionStrong proficiency in Python; familiarity with C++ for performance-critical pathsDeep experience with PyTorch and the Hugging Face ecosystem (Transformers, PEFT, TRL, Datasets)Practical experience with the modern post-training pipeline: SFT, preference optimization, and RL-based methodsUnderstanding of modern model architectures: Mixture of Experts, long-context models, multimodal encodersExperience with inference optimization: quantization, speculative decoding, KV-cache management, batching strategiesFamiliarity with MLOps tooling: experiment tracking (W&B, MLflow), model registries, CI/CD for MLKnowledge of cloud GPU infrastructure (AWS, GCP) and cost-efficient training/serving strategiesStrong problem-solving skills and ability to work in a fast-paced, cross-functional environmentBackground in animal behavior, veterinary science, or bioinformatics is a strong plusNice to HaveExperience with video understanding models and temporal reasoning over long sequencesHands-on experience building agentic AI systems or tool-using LLM workflowsExperience with structured outputs, function calling, and LLM-as-judge evaluation patternsFamiliarity with on-device ML frameworks (Core ML, TensorFlow Lite, ONNX Runtime, ExecuTorch)Experience with synthetic data generation for training data augmentationUnderstanding of distributed training (FSDP, DeepSpeed) for large-scale model trainingKnowledge of AI safety, alignment techniques, and responsible AI practicesExperience with Docker, Kubernetes, and production deployment pipelinesWhy Join UsWork directly on AI that improves animal welfare and pet care. Your models have real-world impact on pets and their ownersFull-stack AI role, from research and training to production serving and on-device deploymentAccess to GPU compute and cloud infrastructure for experimentation and trainingCollaborative team that values shipping over slidesCompetitive salary, equity, and benefitsWe're building the future of intelligent pet care. If you want to push the boundaries of multimodal AI and apply it to a domain that genuinely matters, we want to talk.