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Seekr

AI-driven reliability scoring of online content

Forward Deployed Engineer - DevOps

Applied Machine LearningUpdated on Nov 10
Full-time

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Mathematics, Physics, or Data Science is required; an advanced degree is a plus.
  • At least 6 years of professional experience in software engineering, data engineering, or applied machine learning, with a track record of building and deploying production systems.
  • Hands-on expertise with artificial intelligence and machine learning and large language model frameworks, including PyTorch, Hugging Face, LangChain, and vLLM, including model fine-tuning and agent deployment.
  • Experience designing, deploying, and maintaining production-grade systems that meet enterprise security, compliance, and performance standards.
  • A strong background in on-premises, private cloud, and multi-cloud environments, including AWS, Azure, Google Cloud Platform, containerization, and orchestration with Docker and Kubernetes.
  • Proficiency in at least one modern programming language, such as Python, Java, C++, TypeScript, or JavaScript, with the ability to learn and adapt quickly.
  • Ability to work directly with client stakeholders, including technical teams, business leaders, and end users, to translate needs into deployed solutions.
  • Willingness to travel 25–75%, depending on client and team needs.

Responsibilities

  • Operationalize artificial intelligence proofs of concept by transforming demos and prototypes into robust, production-grade AI systems.
  • Design and deploy data pipelines and retrieval frameworks that prepare enterprise data for large language model training, fine-tuning, and retrieval-augmented generation applications.
  • Fine-tune, evaluate, and deploy large language models and agentic workflows, ensuring outputs remain grounded, explainable, and compliant.
  • Integrate SeekrFlow AI agents with customer environments, containerizing and orchestrating them across cloud, hybrid, and on-premises deployments, including AWS, Azure, Google Cloud Platform, and private cloud.
  • Embed with client engineering teams to debug model behavior, optimize inference performance, and implement monitoring and guardrails for safe operation.
  • Codify best practices into reusable playbooks, evaluation frameworks, and deployment accelerators that scale AI adoption across industries.

Desired Qualifications

  • Familiarity with common graph databases and graph languages, such as Neo4j, AGE, SPARQL, and Cypher.
  • Familiarity with front-end frameworks such as React and the ability to build insightful and engaging application front ends.
  • Experience with continuous integration and continuous delivery pipelines, version control using GitHub or GitLab, and infrastructure as code tools such as Terraform or CloudFormation.
  • Familiarity with vector databases, retrieval-augmented generation architectures, and enterprise data integration patterns.
  • Exposure to monitoring, logging, and observability frameworks for deployed AI and machine learning systems.
  • A background in responsible AI practices and familiarity with Trustworthy AI principles.
  • Experience building custom client-facing applications or agentic workflows from prototype to scalable deployment.
  • Ability to present complex technical concepts clearly to diverse audiences.

About the Company

Seekr

AI-driven reliability scoring of online content

Seekr provides AI-based tools to rate the reliability of online content and reveal its political bias. It delivers the Seekr Score, a reliability rating, plus a Political Lean Indicator, Direct Quotes, and Filters to help users find high-quality information quickly through a privacy-first mobile browser. The AI is trained by journalists and data scientists to analyze content efficiently. Compared with competitors, Seekr combines a trust score with political bias signals and quote-based search features in a privacy-focused mobile app, serving individuals and organizations that need verified information. Its goal is to help users navigate the web, reduce misinformation, and access trustworthy information more efficiently.

Company size
51-200
Company stage
Series B
Total funding
$173M
Headquarters
Reston, VA
Founded
2021

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