AI Engineer / Research Scientist (Senior, Staff), Explainable AI

About the Company Seekr is a leader in explainable and trustworthy artificial intelligence designed to power mission‑critical decisions in enterprises, government, and regulated industries. Our end‑to‑end platform, SeekrFlow™, provides secure, auditable AI solutions across cloud, on‑premises, and edge environments. Trusted by organizations in finance, defense, telecom, and critical infrastructure, we build systems that are transparent, accurate, and compliant. About the Opportunity The first wave of AI focused on scale; today the frontier is reliable AI—systems that are understandable, testable, and dependable in real decisions. At Seekr, explainability is a core product and research problem spanning attribution, interpretability, observability, and contestability. This role sits directly in that high‑impact space, turning state‑of‑the‑art ideas into production capabilities customers can trust. What You’ll Do Design and build explainability capabilities that help users understand why a model or agent produced a given output and what training data, retrieved documents, tools, agent interactions, or internal model mechanisms influenced that result. Design and build contestability capabilities that enable users to challenge AI outputs, capture corrective feedback, and turn contested results into data that improves systems over time. Work on adjacent high‑impact areas such as hallucination detection and mitigation, and continual‑learning agents that can learn from explainability signals and contested outputs. Translate and synthesize promising ideas from current literature into prototypes, and translate validated prototypes into production‑grade features. Contribute across the AI system lifecycle where needed, including model development, inference, deployment, and monitoring. Partner with product, design, and customer‑facing teams to make explainability useful in real workflows, not just technically interesting. Use AI coding assistants effectively and reliably as part of a modern engineering workflow while maintaining strong judgment and code quality. What We’re Looking For Strong background in machine learning and modern AI systems, including LLM/VLMs, agent frameworks, RAG, or adjacent applied ML systems. Ability to move comfortably between research and engineering. Scientists should be able to write production‑grade code when needed; engineers should be able to prototype and pressure‑test systems inspired by state‑of‑the‑art papers. Experience designing experiments and evaluating ambiguous technical trade‑offs. Fluency with AI coding assistants and modern developer workflows. Strong Python and software engineering fundamentals, with comfort in testing, code review, CI/CD, debugging, and performance analysis. Clear communication and strong collaboration across technical and non‑technical partners. Reside near Austin, TX or Reston, VA and able to work 3 days per week in office. Preferred Qualifications, Research Scientist‑Leaning Candidates Master’s or PhD in computer science, machine learning, AI, statistics, or a related field preferred. Experience in explainable and interpretable AI, such as feature attribution methods like LIME and SHAP, example‑ or influence‑based attribution, or mechanistic interpretability. Track record of original technical work, such as publications, patents, open‑source contributions, or research that materially shaped shipped systems. Preferred Qualifications, Engineer‑Leaning Candidates Experience designing end‑to‑end AI systems from data preparation and evaluation through serving, deployment, monitoring, and iteration. Experience with inference and serving stacks such as vLLM, SGLang, or similar systems. Experience optimizing model serving for latency, throughput, batching, caching, memory efficiency, quantization, and cost‑performance trade‑offs. Experience with API/SDK development and building usable platform abstractions for other developers. Experience with Kubernetes‑based deployment, CI/CD, and GitOps workflows such as Argo CD. Experience working with GPU/accelerator environments, containerized ML workloads, and production performance tuning; experience with custom GPU/accelerator kernels for AI workload optimization is a plus. Experience with database and retrieval system design, including relational stores, vector databases, and RAG architectures. Experience with experiment tracking, model/data versioning, evaluation pipelines, observability, and diagnosing production issues in AI systems. Nice to Have Experience designing AI systems with human oversight, review, approval, or override workflows. Familiarity with governance, provenance, security, and auditability requirements for enterprise or government AI. Experience deploying AI across cloud, on‑prem, edge, or air‑gapped environments. Why This Role Matters Explainability is becoming infrastructure, not a side feature. As AI moves deeper into operational, regulated, and business‑critical workflows, the systems that win will be the ones people can interrogate, validate, and defend. This role is a chance to help define that standard at a company built around trusted AI from the start. Company Benefits Meaningful Mission & Impact - Work with a deeply talented, collaborative team solving some of the toughest AI challenges that matter. Equity Ownership – RSUs that let you share directly in Seekr’s long‑term success and growth. Time Off That Respects Real Life – Unlimited PTO plus 14 paid company holidays to truly recharge. Work Your Way – A flexible hybrid work environment with offices in Reston, VA and Austin, TX, plus remote options and flexible working hours. Competitive Total Rewards – A role‑appropriate compensation structure that supports long‑term growth, including base salary, bonuses, or commission plans depending on role. 401(k) with Company Match – Build your future with a retirement plan that includes employer matching. Comprehensive Health & Wellness – Medical, dental, vision, and life insurance coverage starting day one—for you and your family. Parental Leave – Paid parental leave to support employees as they welcome a new child through birth, adoption, or foster placement. #J-18808-Ljbffr Seekr