Applied AI Scientist – Senior/Staff

This is a fully remote position, open to applicants in United States.

📋 Description

• Conduct research, develop, and assess machine learning techniques to enhance product functionalities and improve customer outcomes.

• Create experiments to evaluate new model architectures, training methodologies, data strategies, and system designs.

• Modify foundation models through fine-tuning, post-training adjustments, prompt optimization, retrieval, or other methodologies.

• Establish evaluation frameworks and benchmarks to assess model quality, reliability, safety, and performance.

• Construct prototypes and proofs of concept that showcase emerging AI methodologies.

• Collaborate with AI/ML engineers and software developers to convert successful experiments into production-ready systems.

• Enhance model accuracy, reasoning capabilities, latency, efficiency, robustness, and cost-effectiveness.

• Curate, generate, and assess datasets for training, fine-tuning, and model evaluation purposes.

• Examine model failures, edge cases, and unexpected behaviors to uncover opportunities for improvement.

• Remain updated on relevant research and pinpoint advancements that can deliver practical value to products.

• Convey findings, trade-offs, and technical recommendations to product, engineering, and executive stakeholders.

• Mentor fellow scientists and contribute to the research culture, technical standards, and the AI roadmap.

• Publish research, engage in open-source projects, or represent the company in the broader technical community as appropriate.

• Submit an application to become a part of SignalFire’s Talent Ecosystem.

• SignalFire reviews applications continuously and may link suitable candidates with portfolio-company talent partners or leaders.

⛳️ Requirements

• Over 5 years of experience in machine learning, artificial intelligence, applied research, or a related technical domain.

• Strong background in deep learning, statistics, optimization, and experimental design.

• Experience in developing or modifying 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 recognition.

• Proficient in Python and modern machine learning frameworks like PyTorch, TensorFlow, or JAX.

• Experience with model training, fine-tuning, post-training evaluation, or inference processes.

• Ability to design rigorous experiments and derive sound conclusions from incomplete or ambiguous results.

• Proven track record of converting research concepts into prototypes, production systems, or measurable product enhancements.

• Capability to collaborate effectively with research, engineering, product, and domain specialists.

• Strong written and verbal communication skills, including the ability to clearly explain complex technical ideas.

• Candidates at the staff level may be expected to define research direction, lead cross-functional initiatives, and influence broader AI strategies.

• An advanced degree in computer science, machine learning, statistics, mathematics, or a related field may be preferred; equivalent practical experience may also be considered.

• Familiarity with technologies such as Python, PyTorch, TensorFlow, JAX, Hugging Face, scikit-learn, large language models, transformers, multimodal models, diffusion models, reinforcement learning, recommendation systems, fine-tuning, reinforcement learning from feedback, preference optimization, distillation, synthetic data, prompt optimization, retrieval-augmented generation, agents, tool usage, 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

• Enhanced visibility into exclusive early-stage opportunities that may not be publicly available.

• Potential access to future opportunities across SignalFire’s portfolio companies.

• Opportunities to publish research, contribute to open-source projects, or represent the company in the broader technical community as appropriate.