Principal Machine Learning Engineer I Hybrid in Horsham, PA or Remote EST Preferred
About The Position
LexisNexis Reed Technology has partnered with the U.S. Patent and Trademark Office (USPTO) for over 50 years, providing secure, scalable, and high-quality patent data processing solutions. The team transforms complex patent submissions into standardized, searchable outputs for examiner workflows and public dissemination. Operating in a regulated environment with strict security, large data volumes, and complex business rules, the focus is on modernizing legacy workflows through automation, AI, and platform transformation to enhance efficiency, accuracy, and cost-effectiveness. This role is for a hands-on Principal AI Engineer who can design and build production-grade AI solutions, with a growth path into a broader AI Architect role. The ideal candidate is an experienced AI developer or technical lead with strong engineering depth, modern AI architecture understanding, and the readiness to expand influence across platforms, products, and delivery teams. The Principal AI Engineer will collaborate with product managers, architects, data scientists, software engineers, security teams, and government stakeholders to translate mission and business needs into secure, scalable, and reusable AI capabilities. The role will initially involve solution design and hands-on implementation, with increasing responsibility for architecture standards, technical strategy, governance, and cross-team alignment.
Requirements
- Bachelor’s degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience.
- Significant professional software engineering experience, including experience delivering production applications or platforms.
- Hands-on experience developing AI, machine-learning, or data-intensive solutions.
- Proficiency in Python and experience with APIs, cloud services, data pipelines, software development practices, and source control.
- Experience with modern generative-AI patterns, such as large language models, retrieval-augmented generation, embeddings, vector search, tool use, structured outputs, or AI agents.
- Understanding of cloud-native architecture, system integration, identity and access management, observability, and secure development practices.
- Ability to evaluate technical alternatives and explain architecture decisions and tradeoffs.
- Experience working across product, engineering, data, security, and business teams.
- Strong written and verbal communication skills.
- Ability to satisfy applicable government background, suitability, or contractual requirements.
Nice To Haves
- Experience delivering technology solutions for U.S. federal, state, or local government customers.
- Experience working in government contracting, regulated environments, or programs involving sensitive data.
- Familiarity with government security and compliance frameworks, such as NIST, FedRAMP, FISMA, or agency-specific controls.
- Experience with one or more major cloud platforms, particularly AWS, Microsoft Azure, or Google Cloud.
- Experience with AI orchestration frameworks, model gateways, vector databases, evaluation platforms, MLOps, or LLMOps.
- Understanding of model evaluation, prompt engineering, fine-tuning, data governance, and responsible-AI practices.
- Experience moving AI proofs of concept into production.
- Experience supporting technical proposals, RFIs, RFPs, solution demonstrations, or customer workshops.
- Prior technical leadership, mentoring, or architecture-review experience.
- Relevant cloud, architecture, security, data, or AI certifications.
Responsibilities
- Design, prototype, and implement AI-powered applications, services, agents, and workflows.
- Translate business, user, and government mission requirements into practical technical solutions.
- Develop solutions using large language models, retrieval-augmented generation, machine learning, natural language processing, computer vision, or other relevant AI technologies.
- Build reusable AI components, services, APIs, evaluation frameworks, and reference implementations.
- Integrate AI capabilities with enterprise platforms, data sources, workflows, and existing applications.
- Balance rapid experimentation with the engineering discipline required for secure, reliable production systems.
- Evaluate models, platforms, frameworks, and vendors based on performance, cost, security, scalability, and mission fit.
- Contribute to solution architectures covering applications, models, data, integrations, infrastructure, security, and operational monitoring.
- Partner with senior architects to establish AI architecture patterns, guardrails, standards, and reference architectures.
- Help teams make informed decisions regarding commercial, open-source, and internally developed AI capabilities.
- Identify opportunities to create shared AI services and reusable capabilities across products, contracts, and government agencies.
- Participate in architecture reviews and clearly document technical decisions, tradeoffs, assumptions, and risks.
- Provide technical guidance, code reviews, mentoring, and hands-on support to engineering and data science teams.
- Grow into ownership of end-to-end AI solution architecture and broader technical strategy.
- Support technical discovery sessions, demonstrations, proofs of concept, proposals, RFIs, and RFP responses.
- Communicate complex AI concepts, limitations, risks, and tradeoffs clearly to both technical and non-technical audiences.
- Help move successful prototypes into secure, supportable, and scalable production capabilities.
- Stay informed about evolving government AI policies, standards, acquisition practices, and responsible-AI expectations.
- Incorporate security, privacy, accessibility, explainability, auditability, and human oversight into solution designs.
- Establish appropriate evaluation methods for accuracy, relevance, groundedness, bias, safety, and reliability.
- Design controls for model and prompt versioning, data lineage, access management, logging, monitoring, and traceability.
- Partner with cybersecurity, legal, privacy, compliance, and governance teams throughout the solution lifecycle.
- Ensure solutions align with applicable organizational policies, contractual obligations, and government requirements.
- Design human-in-the-loop controls based on the risk and impact of the decisions supported or performed by AI.
Benefits
- Comprehensive, multi-carrier program for medical, dental and vision benefits
- 401(k) with match and an Employee Share Purchase Plan
- Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
- Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
- Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits
- Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
- Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice
- Shared parental leave
- Study assistance
- Sabbaticals
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Principal
