AI Engineer/Scientist, Staff

Seekr; Menlo Park (CA); Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Equity Ownership

Unlimited PTO

Hybrid work environment

401(k) Matching

Comprehensive Health & Wellness

Job summary

Seekr is hiring for a senior AI engineering / research scientist role in the United States. You will work at the intersection of research and engineering to make explainable and trustworthy AI deployed in real workflows.

The role supports hybrid work across Reston, VA and Austin, TX while emphasizing rigorous debugging, testing, and collaboration with product teams. Qualifications include 8+ years in AI engineering/research, strong ML systems background, and proficiency in Python, CI/CD, and AI

Qualifications

• 8+ years of AI engineering and/or AI research experience or equivalent.
• Strong background in ML systems including LLM/VLMs and RAG.
• Ability to move between research and engineering.
• Production-grade coding when needed; prototype-driven mindset.
• Experience designing experiments and evaluating tradeoffs.
• Fluency with AI coding assistants and modern dev workflows.
• Strong Python and software engineering fundamentals; testing and CI/CD.

Responsibilities

• Design explainability capabilities so users understand outputs and influences.
• Build contestability features to capture feedback and improve systems.
• Address hallucination detection and continual-learning signals.
• Translate literature ideas into prototypes and production-grade features.
• Contribute across model development, inference, deployment, and monitoring.
• Collaborate with product, design, and customer-facing teams.
• Use AI coding assistants effectively within a modern workflow.

Skills

LLM/VLMs

Python

CI/CD

Debugging

Communication

Education

Master’s or PhD in CS/ML/AI

Tools

Kubernetes

Argo CD

Job description

Seekrbuilds trusted AI for mission-critical decisions. Our platform helps organizations build, govern, and deploy secure, explainable AI rooted in their own data across cloud, on-premises, edge, and air-gapped environments. We care deeply about transparency, auditability, and defensibility because high-stakes AI is only useful when people can understand and trust how it behaves.

The first wave of AI was about scale. The frontier now is reliable AI: systems that are not only capable, but understandable, testable, and dependable in real decisions. AtSeekr, explainability is not a reporting layer added after deployment; it is a core product and research problem spanning attribution and interpretability, observability, and contestability. This role sits directly in that high-impact space, helping turnstate-of-the‑artideas into production capabilities customers can trust.

We are open to candidates from either research scientist or engineering backgrounds. Success in this role requires strength in onedomain, andworkingproficiencyin the other.

Duties and Responsibilities

• 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.

Qualifications and Skills Required:

• 8+ years of experience in AI engineering and/or AI research/science roles, or equivalent relevant experience.
• 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 here should be able to write production‑grade code when needed; engineers here should be able to prototype and pressure‑test systems inspired by state‑of‑the‑art.
• Experience designing experiments and evaluating ambiguous technical tradeoffs.
• Fluency with AI coding assistants and the modern developer workflows they enable.
• 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, ora relatedfield 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:

• Designs end‑to‑end AI systems spanning data preparation, evaluation, serving, deployment, monitoring, and iteration.
• Works with inference and serving stacks such as vLLM, SGLang, or similar systems.
• Optimizes model serving for latency, throughput, batching, caching, memory efficiency, quantization, and cost/performance tradeoffs.
• Develops APIs/SDKs and builds usable platform abstractions for other developers.
• Deploys with Kubernetes‑based workflows, CI/CD, and GitOps tools such as Argo CD.
• Works within GPU/accelerator environments, containerized ML workloads, and production performance tuning; familiarity with custom GPU/accelerator kernels for AI workload optimization is a plus.
• Designs database and retrieval systems, including relational stores, vector databases, and RAG architectures.
• Builds experiment tracking, model/data versioning, and evaluation pipelines, with strong observability and production issue diagnosis in AI systems.

#LI-CT1

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. SeekrFlow™, our end‑to‑end AI platform, provides secure, auditable AI solutions tailored to sectors where transparency, accuracy, and compliance are paramount. Available across cloud, on‑premises, and edge environments, SeekrFlow reduces bias, strengthens data integrity, and simplifies model oversight so organizations can rely on trusted AI decisions in high‑stakes settings that impact society’s most sensitive and vital systems. Trusted by leading enterprises and government agencies, we partner with defense, finance, telecom, and critical infrastructure leaders to enable AI solutions that drive real‑world results with unmatched transparency and control. We are a team of strategic thinkers and problem‑solvers tackling the toughest challenges facing critical infrastructure and global enterprises through best‑in‑class AI models and customer deployment. Our team operates with unwavering commitment to our core values and mission:

• We are driven by outcomes—our customers’ success is what we strive for every day.
• We believe trust is earned, which is why we build explainability and transparency into the entire AI lifecycle.
• We take our responsibility to deliver secure AI seriously.
• We believe innovation drives progress—we are building the technologies that power the systems our society depends on.

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.

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