AI Research Engineer – Generative AI at NeuroPace Inc

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

04 Jul, 26

Salary

175000.0

Posted On

06 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

LLM training, Multimodal models, RAG systems, Python, TypeScript, PyTorch, TensorFlow, HuggingFace, Agentic systems, Vector indexing, Distributed training, Machine learning, Data pipelines, Inference optimization, Observability, Prompt engineering

Industry

Medical Equipment Manufacturing

Description

Based in Mountain View, CA., NeuroPace is a commercial-stage medical device company focused on transforming the lives of people suffering from epilepsy by reducing or eliminating the occurrence of debilitating seizures. Its novel and differential RNS System is the first and only commercially available, brain-responsive platform that delivers personalized, real-time treatment at the seizure source. At NeuroPace, employees are our greatest asset. We are continually searching for solution-oriented individuals who can bring energy and creativity to our growing workforce. At NeuroPace, our success depends upon our ability to recruit and retain the most talented, enthusiastic and dedicated people we can find and providing them with a dynamic and challenging environment in which to thrive. We’re seeking an AI Research Engineer to develop multimodal LLMs, reasoning agents, and large‑scale RAG systems. In this role, your work will directly help people living with neurological disease; you’ll be part of a fast-moving group dedicated to using AI tools to accelerate impact of an FDA-approved implantable device. You’ll own model training pipelines, high‑throughput data and indexing systems, and retrieval‑augmented generation powering production applications. Ideal candidates have experience training large multimodal models, building scalable data/feature stores, and shipping agentic systems with strong observability and safety. The position must be based in the Bay Area and with the ability to commute to our NeuroPace Mountain View office three days a week. Key Responsibilities Model Training & Inference Train/fine‑tune LLMs and multimodal models (text/vision/audio; bonus: neural/ECoG). Use SFT, DPO/ORPO, RLHF/RLAIF, and parameter‑efficient tuning (LoRA/QLoRA). Build agentic systems (tool use, planning, memory, reasoning) with attention to latency, safety, and cost. Optimize inference: quantization, graph/tensor optimizations, speculative decoding, distillation, caching. Data & Indexing Build fast pipelines for ingest, feature extraction, multimodal alignment, and dataset curation. Design billion‑scale indexing (vector, hybrid sparse+dense, graph‑based). Implement observability: lineage, drift, coverage, bias, differential performance, cost. RAG & Knowledge Systems Build production RAG (chunking, hybrid search, reranking, context optimization). Maintain continuous refresh pipelines (incremental indexing, TTL, schema evolution). Integrate ontologies/knowledge graphs for grounding and attribution. Evaluation, Safety & Reliability Develop structured evaluations for faithfulness, factuality, consistency, and multimodal alignment. Implement guardrails: prompt hardening, policy filters, PII/PHI handling, output verification. Run A/B tests; define metrics for quality, latency, and cost. Platform & Collaboration Partner with infra for distributed training (FSDP/ZeRO, multi‑GPU/TPU), registries, and ML CI/CD. Mentor engineers and contribute to long‑term technical strategy. Requirements Minimum Qualifications 2+ years in ML/AI (or equivalent impact). Master’s in CS or related field, or equivalent experience. Hands‑on LLM/multimodal training (PyTorch/TensorFlow/HuggingFace/SageMaker). Strong engineering skills: Python, TypeScript, APIs, testing, profiling, and observability. Preferred Qualifications 4+ years in ML/AI and production ML system experience. Experience shipping agentic systems with planning, tool use, schemas, memory, and guardrails. Multimodal expertise: CLIP‑style contrastive models, BLIP/LLaVA/Flamingo, Whisper/NeMo, video, neural signals. Production RAG (chunking, grounding, hallucination mitigation, cost/latency tuning). Distributed training (FSDP/DeepSpeed/ZeRO), mixed precision, checkpointing. Information retrieval: query understanding, retrieval‑aware generation, knowledge graphs. Causal inference or counterfactual evaluation for scientific/biomedical ML. $135K-$175K Base - Compensation will be determined based on several factors, including but not limited to skill set, years of experience, and geographic location. NeuroPace is proud to be an equal opportunity employer and values the contributions of our culturally diverse workforce.San Francisco and Los Angeles applicants: The Company will consider for employment qualified applicants with Criminal Histories in a manner consistent with the requirements of the Los Angeles Fair Chance in Hiring Ordinance or the San Francisco Fair Chance Ordinance (as applicable) Benefits Medical, Dental & Vision Insurance Voluntary Life 401K RSU 529 plan ESPP Program Health & Wellness Program Generous Paid Time Off plus eleven paid holidays FSA & Commuter Benefits NeuroPace is proud to be an equal opportunity employer and values the contributions of our culturally diverse workforce. San Francisco and Los Angeles applicants: The Company will consider for employment qualified applicants with Criminal Histories in a manner consistent with the requirements of the Los Angeles Fair Chance in Hiring Ordinance or the San Francisco Fair Chance Ordinance (as applicable) PRIVACY NOTICE: NeuroPace takes its responsibility to protect your personal information seriously, and it uses reasonable safeguards to avoid unauthorized use or disclosure of it, and inadvertent loss or impermissible alteration of it. NeuroPace complies with all applicable federal and state laws and regulations that govern the handling of your personal information. If you would like more detailed information on NeuroPace’s privacy policies, please refer to neuropace.com/privacy/ for reference. NeuroPace retains candidate resumes and applications in its files for future reference and/or consideration for other available job postings. If you do not wish for your resume and applications materials to be retained in NeuroPace files, or wish to obtain a listing of any personal information that NeuroPace has stored about you, please contact us at privacy@neuropace.com.

Responsibilities

The AI Research Engineer will develop multimodal LLMs, reasoning agents, and large-scale RAG systems to support an FDA-approved implantable medical device. Responsibilities include owning model training pipelines, optimizing inference, and building scalable data indexing systems.