Senior AI Engineer (Healthcare application)
Engineering Python AI/Artificial Intelligence Machine Learning
年収
Location
Benefits
13ヶ月目の給与
その他の福利厚生
Job Overview And Responsibility
Prevana is looking for a Senior AI Engineer to lead the design, development, and deployment of AI features that power our mobile app experience. You will own the end‑to‑end lifecycle of models behind our in‑app intelligence, from data and experimentation to production and continuous improvement This is a hands-on, high-impact role for someone who loves training models, running experiments, and making them work in production. - Own AI feature delivery end-to-end: lead the architecture, implementation, and rollout of LLM/ML capabilities that power core app experiences (symptom Q&A, next-step guidance, personalization, and smart recommendations), from prototype → production → iteration. - Model development & adaptation: fine-tune and evaluate large language models (OpenAI, Gemini, open-source, etc.) for our domain, including prompt engineering, RAG pipelines, and safety/guardrail systems. - Data pipeline ownership: design and maintain data pipelines for collection, cleaning, labeling, and feature engineering, ensuring data quality and compliance with privacy requirements. - Design the intelligence stack: establish evaluation frameworks, metrics, and monitoring for model performance, reliability, and UX impact in production. - Production inference & integration: build scalable, low-latency inference services and APIs that integrate AI models with our mobile apps and backend systems. - Performance & cost optimization: optimize models for performance and cost, including quantization, distillation, and on-device vs. server-side tradeoffs. - MLOps & operational excellence: apply best practices in MLOps, experimentation, and code quality. - Cross-functional technical leadership: translate product requirements into robust AI solutions, working closely with product managers, designers, and mobile engineers to ship features that delight users. - Stay ahead pragmatically: stay current with state-of-the-art research in LLMs, NLP, and mobile AI and bring relevant advancements into the product roadmap
Required Skills and Experience
- 4+ years of experience in machine learning / AI engineering, with at least 2 years working directly with NLP or LLM-driven products in production. - Strong programming skills in Python and one strongly typed language, with a track record of shipping production systems. - Deep hands-on experience with modern ML/LLM frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face, LangChain/LlamaIndex, vector databases). - Proven experience fine-tuning and deploying LLMs or other deep learning models, including evaluation, A/B testing, and monitoring. - Solid understanding of data structures, algorithms, distributed systems, and cloud platforms (e.g., AWS, GCP) as they relate to ML workloads. - Experience building or integrating APIs and microservices that serve ML models at scale. - Strong product mindset and ability to work cross-functionally, balancing technical excellence with delivery speed and user experience. - Enjoy working in a fast, messy, ambitious environment where specs are not always final, and you help design the answer.
Why Candidate should apply this position
- Ownership of core intelligence: You’ll lead the modeling direction for Parkinson’s Disease-focused foundation models and scientific predictors that sit at the heart of our end-to-end discovery engine—not side experiments. - High-impact mission: Your work directly affects how quickly we can generate and prioritize better Parkinson’s Disease drug candidates, with real-world downstream validation. - GPU-first build environment: Access to modern GPU infrastructure and an engineering stack designed for training + high-throughput inference, with strong MLOps support for deployment. - End-to-end shipping culture: You’ll take models from idea → experiment → evaluation → production. We value measurable impact, reproducibility, and decision- grade reliability. - Annual leave - SHUI and Health Insurance - Bonuses and 13th-month salary. - Other benefits are considered on a case-by-case basis
Preferred skills and experiences
- Experience with mobile-centric AI: on-device ML, model compression/quantization for mobile, or integrating AI into iOS/Android applications. - Prior work on conversational agents, copilots, RAG systems, or recommendation engines in consumer apps. - MLOps tooling: MLflow, Weights & Biases, Vertex AI/SageMaker, CI/CD for models. - Experience working in an early-stage startup or fast-moving product environment
Report to
Management team
Interview process
Phone screen -> Assignment -> Technical round
