Applied AI Scientist – Senior/Staff

SignalFire

SignalFire talent network connecting senior applied AI scientists and researchers with VC-backed startups. Developing advanced machine-learning capabilities, prototypes, evaluations, and production AI systems.

Posted 8/5/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning and artificial intelligence, with a strong foundation in deep learning, statistics, and experimental design. Proficient in developing and adapting models for real-world applications, while effectively communicating technical concepts to diverse stakeholders.

Highest-signal resume keywords

Machine Learning ExpertiseDeep Learning ProficiencyPython ProgrammingModel Evaluation and Fine-TuningCollaboration with Cross-Functional Teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningNatural Language ProcessingGenerative AIComputer VisionReinforcement LearningModel TrainingExperimental DesignStatistical AnalysisOptimization

Soft Skills

Strong Communication SkillsMentoringCollaboration

Tools & Technologies

PythonPyTorchTensorFlowJAXHugging FaceScikit-learnKubernetesSparkDatabricksSnowflake

Industry Keywords

Artificial IntelligenceMachine Learning FrameworksModel EvaluationPrototypingData StrategiesAI RoadmapResearch CultureOpen-Source ContributionsModel RobustnessProduct Applications

Tech Stack

Tools & technologies

KubernetesPythonPyTorchScikit-LearnSparkTensorflow

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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