Benjamin Reavill

AI Evaluation Engineer $160,000 - $180,000 Remote (US-based)Are you passionate about shaping how AI is deployed safely, reliably, and at scale? This is a rare opportunity to join a mission-driven tech company as their first AI Evaluation Engineer, a foundational role where you’ll design, build, and own the evaluation systems that safeguard every AI-powered feature before it reaches the real world.This organization builds AI-enabled products that directly helps governments, nonprofits, and agencies deliver financial support to people who need it most. As AI capabilities race forward, ensuring these systems are safe, accurate, and resilient is critical. That’s where you come in.You won’t just be testing models, you’ll be creating the frameworks, pipelines, and guardrails that make advanced LLM features safe to ship. You’ll collaborate with engineers, PMs, and AI safety experts to stress test boundaries, uncover weaknesses, and design scalable evaluation systems that protect end users while enabling rapid innovation. What You’ll DoOwn the evaluation stack – design frameworks that define “good,” “risky,” and “catastrophic” outputs.Automate at scale – build data pipelines, LLM judges, and integrate with CI to block unsafe releases.Stress testing – red team AI systems with challenge prompts to expose brittleness, bias, or jailbreaks.Track and monitor – establish model/prompt versioning, build observability, and create incident response playbooks.Empower others – deliver tooling, APIs, and dashboards that put eval into every engineer’s workflow. Requirements:Strong software engineering background (TypeScript a plus)Deep experience with OpenAI API or similar LLM ecosystemsPractical knowledge of prompting, function calling, and eval techniques (e.g. LLM grading, moderation APIs)Familiarity with statistical analysis and validating data quality/performanceBonus: experience with observability, monitoring, or data science tooling

Senior Deep Learning Scientist $160,000 - $250,000 (DOE) Onsite – New Haven, Connecticut A cutting-edge biotech startup is seeking a Senior Deep Learning Scientist to join their team. This innovative company is pioneering a first-of-its-kind platform to conduct preclinical studies, aiming to revolutionize the understanding and treatment of neurological diseases.As a Senior Deep Learning Scientist, you will play a pivotal role in designing and implementing AI models that integrate complex biological signals. You'll be at the forefront of pioneering work in areas such as generative graph representation learning, contributing to the development of novel AI architectures tailored to the intricacies of human brain biology.Key Responsibilities:Design, develop, and deploy state-of-the-art deep learning models for analyzing multi-modal biological data.Develop deep learning architectures incorporating biological inductive biases, and explore generative graph representation learning to uncover novel patterns in brain data.Work closely with bioinformatics, experimental biology, and engineering teams to integrate multi-modal datasets into cohesive AI frameworks.Optimize deep learning pipelines for petabyte-scale datasets and ensure models are scalable on high-performance computing infrastructures.Publish research findings and present at scientific conferences to contribute to the broader AI and biomedical communities. Requirements:PhD or Post-doc in Computer Science, Machine Learning, or a related STEM field with a strong demonstrated track record of applying deep learning to biological problems.The ability to translate conceptual research frameworks into deployable architectures.Comfort working across research and applied implementation.Proven experience with GNNs. Experience with generative graph representation learning is a significant plus.Expertise in PyTorch with the ability to build and deploy scalable models.Familiarity with developing production-quality pipelines, cloud computing, and model deployment best practices.Demonstrated ability to research and implement novel deep learning architectures tailored to complex STEM datasets.Experience with high-performance computing (HPC) environments or distributed training techniques for large-scale GNN models. Apply now or reach out to Ben at benjamin@deeprec.ai to learn more!