Applied AI Scientist – Senior/Staff

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SignalFire

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2012

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

SignalFire is a venture capital firm built on technology and data, dedicated to supporting growth for early-stage companies through advanced AI tools and seasoned sector expertise. They focus on providing unparalleled support to their portfolio companies, combining in-house AI capabilities with tailored advisory programs across multiple sectors such as healthcare, fintech, cybersecurity, and more.

📋 Description

• Research, develop, and evaluate machine learning methods that improve product capabilities and customer outcomes • Design experiments to test new model architectures, training approaches, data strategies, and system designs • Adapt foundation models through fine-tuning, post-training, prompt optimization, retrieval, or other techniques • Develop evaluation frameworks and benchmarks for model quality, reliability, safety, and performance • Build prototypes and proofs of concept demonstrating emerging AI techniques • Partner with AI/ML engineers and software engineers to translate successful experiments into production systems • Improve model accuracy, reasoning, latency, efficiency, robustness, and cost • Curate, generate, and evaluate datasets for training, fine-tuning, and model assessment • Investigate model failures, edge cases, and unexpected behavior to identify improvement opportunities • Stay current with relevant research and identify advances that can create practical product value • Communicate findings, tradeoffs, and technical recommendations to product, engineering, and executive stakeholders • Mentor other scientists and contribute to research culture, technical standards, and the AI roadmap • Publish research, contribute to open-source projects, or represent the company in the broader technical community where appropriate • Submit an application to join SignalFire’s Talent Ecosystem • SignalFire reviews applications on an ongoing basis and may connect matched candidates with portfolio-company talent partners or leaders

🎯 Requirements

• 5+ years of experience in machine learning, artificial intelligence, applied research, or a related technical field • Strong foundation in deep learning, statistics, optimization, and experimental design • Experience developing or adapting models for real-world product applications • Expertise in one or more of natural language processing, generative AI, computer vision, multimodal learning, reinforcement learning, recommendation systems, or speech • Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow, or JAX • Experience with model training, fine-tuning, post-training, evaluation, or inference • Ability to design rigorous experiments and draw sound conclusions from incomplete or ambiguous results • Track record of translating research concepts into prototypes, production systems, or measurable product improvements • Ability to collaborate with research, engineering, product, and domain experts • Strong written and verbal communication skills, including explaining complex technical concepts clearly • Staff-level candidates may be expected to define research direction, lead cross-functional initiatives, and influence broader AI strategy • Advanced degree in computer science, machine learning, statistics, mathematics, or a related field may be preferred; equivalent applied experience may be considered • Technologies may include Python, PyTorch, TensorFlow, JAX, Hugging Face, scikit-learn, large language models, transformers, multimodal models, diffusion models, reinforcement learning, recommendation and ranking systems, fine-tuning, reinforcement learning from feedback, preference optimization, distillation, synthetic data, prompt optimization, retrieval-augmented generation, agents, tool use, structured generation, reasoning systems, model routing, evaluation, benchmarking, red teaming, interpretability, model observability, Spark, Databricks, Snowflake, vector databases, distributed training, GPUs, Kubernetes, and major proprietary or open-source foundation models

🏖️ Benefits

• Profile visibility into exclusive early-stage opportunities that may not be publicly listed • Potential access to future opportunities across SignalFire’s portfolio companies • Opportunity to publish research, contribute to open-source projects, or represent the company within the broader technical community where appropriate