AI Scientist and Researcher

• 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 that demonstrate the potential of 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 used for training, fine-tuning, and model assessment
• Investigate model failures, edge cases, and unexpected behavior to identify opportunities for improvement
• Stay current with relevant research and determine which advances can create practical product value
• Communicate findings, tradeoffs, and technical recommendations to product, engineering, and executive stakeholders
• Mentor other scientists and contribute to the company’s research culture, technical standards, and AI roadmap
• Publish research, contribute to open-source projects, or represent the company within the broader technical community where appropriate, * Models & Techniques: Large language models, transformers, multimodal models, diffusion models, reinforcement learning, recommendation and ranking systems
• Model Adaptation: Fine-tuning, reinforcement learning from feedback, preference optimization, distillation, synthetic data, prompt optimization
• AI Systems: Retrieval-augmented generation, agents, tool use, structured generation, reasoning systems, model routing
• Evaluation & Experimentation: Offline and online evaluation, human evaluation, benchmarking, red teaming, interpretability, model observability
• Data & Infrastructure: Spark, Databricks, Snowflake, vector databases, distributed training, GPUs, Kubernetes
• Models & Platforms: OpenAI, Anthropic, Google, Meta, open-source foundation models, and proprietary model architectures

What Happens Next?

1. Submit your application to join SignalFire’s Talent Ecosystem.
2. We review applications on an ongoing basis to identify strong candidates.
3. If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
4. No match yet? We’ll keep your profile on file for future Senior and Staff Applied AI Scientist and Researcher roles across our portfolio.

? Passionate about advancing the capabilities and real-world applications of artificial intelligence ? Experienced in developing, adapting, and evaluating modern machine learning models ? Excited to translate research and experimentation into production-ready product capabilities ? Comfortable operating at the intersection of research, engineering, product, and customer needs ? Interested in solving open-ended technical problems in fast-moving startup environments, * 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 areas such as 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 closely with research, engineering, product, and domain experts
• Strong written and verbal communication skills, including the ability to explain 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, although equivalent applied experience may be considered

At SignalFire , we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.

We’re looking to connect with exceptional Senior and Staff Applied AI Scientists and Researchers who are excited about developing advanced AI capabilities, solving complex technical problems, and translating emerging research into differentiated products.

By joining SignalFire’s Talent Network , your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.