AI Engineer - AI Department

Designlibro•San Jose, CA

3d•$140,000 - $230,000

About The Position

We 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.

Requirements

Bachelor's or Master's degree in Computer Science, AI/ML, Electrical Engineering, or a related field
2+ years of hands-on experience training and deploying ML models in production
Strong proficiency in Python; familiarity with C++ for performance-critical paths
Deep 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 methods
Understanding of modern model architectures: Mixture of Experts, long-context models, multimodal encoders
Experience with inference optimization: quantization, speculative decoding, KV-cache management, batching strategies
Familiarity with MLOps tooling: experiment tracking (W&B, MLflow), model registries, CI/CD for ML
Knowledge of cloud GPU infrastructure (AWS, GCP) and cost-efficient training/serving strategies
Strong problem-solving skills and ability to work in a fast-paced, cross-functional environment
Background in animal behavior, veterinary science, or bioinformatics is a strong plus

Nice To Haves

Experience with video understanding models and temporal reasoning over long sequences
Hands-on experience building agentic AI systems or tool-using LLM workflows
Experience with structured outputs, function calling, and LLM-as-judge evaluation patterns
Familiarity with on-device ML frameworks (Core ML, TensorFlow Lite, ONNX Runtime, ExecuTorch)
Experience with synthetic data generation for training data augmentation
Understanding of distributed training (FSDP, DeepSpeed) for large-scale model training
Knowledge of AI safety, alignment techniques, and responsible AI practices
Experience with Docker, Kubernetes, and production deployment pipelines

Responsibilities

Fine-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 monitoring
Build multimodal AI pipelines that combine video, audio, weight sensor data, and other sensor modalities for real-time animal behavior analysis
Design 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-making
Optimize 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 video
Develop 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 hardware
Monitor model performance in production, set up drift detection, and maintain model versioning and rollback processes