Principal Machine Learning Engineer
About the job
- At least 10 years of Machine Learning or Software Engineering experience.
- A master's degree or bachelor's degree is required.
- A strong software engineering background with experience building system designs and architecting AI features or products that serve a large number of users and handle large volumes of unstructured data is required.
- Experience deploying machine learning systems to production is required.
- Provide architectural direction and code-level guidance.
- Establish engineering best practices for machine learning system design, testing, and deployment.
- Conduct design reviews, performance reviews, and technical roadmap planning.
- Architect distributed machine learning systems serving multiple global products.
- Standardize infrastructure patterns for large language model serving and retrieval systems.
- Define and implement enterprise-ready agentic frameworks.
- Architect multi-step reasoning systems.
- Lead decisions on deterministic workflows versus autonomous agents.
- Implement guardrails, safety layers, and traceability mechanisms.
- Develop evaluation frameworks to measure reasoning quality, hallucination rates, and reliability.
- Establish continuous integration and continuous delivery standards for machine learning lifecycle management.
- Ensure compliance with enterprise data governance and responsible artificial intelligence standards.
- A computer science degree is highly desirable.
About the company
LexisNexis Risk Solutions provides data, analytics, and decision tools to help organizations assess and manage risk across many industries. Its offerings combine large data sets with advanced analytics to support better decisions, improve operations, and protect consumers. By covering sectors like financial services, government, healthcare, insurance, retail, and public safety, the company helps customers evaluate likelihoods of risk, detect issues, and act more efficiently. The goal is to turn data into actionable insight that reduces risk, increases operational efficiency, and supports compliant, informed decision-making for its clients.
Company Size
5,001-10,000
Company Stage
N/A
Total Funding
N/A
Headquarters
Alpharetta, Georgia
Founded
1997
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Simplify's Take
What believers are saying
- Arizona's Digital Birth Credential rollout expanded statewide June 1, 2026.
- Cytora, Epic, and Agenium integrations widen distribution across commercial, healthcare, and life insurance.
- 2026 reports show rising fraud, higher home severity, and SNAP losses $4.29 per dollar.
What critics are saying
- Choksi v. LexisNexis Risk Solutions and Ioane v. LexisNexis Risk Solutions expand FCRA exposure.
- Scroggins settled for $13.5 million after false deceased reports; data quality remains a liability.
- TransUnion, Experian Health, and Socure target adjacent identity and fraud budgets aggressively.
What makes LexisNexis Risk Solutions unique
- RELX-backed LexisNexis Risk Solutions spans fraud, insurance, healthcare, and government workflows.
- Emailage Adaptive, launched October 1, 2026, self-calibrates and cuts false positives 80%.
- FedRAMP In Process status and TxRAMP certification strengthen public-sector trust.
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Benefits
Health Insurance
401(k) Company Match
Wellness Program
Short-and-Long Term Disability
Life Insurance
Family Planning Benefits
Health Savings Account/Flexible Spending Account
Paid Vacation
Company News
LexisNexis Risk Solutions has launched Emailage Adaptive, a self-calibrating AI fraud detection solution that continuously learns from each organisation's unique fraud patterns without manual intervention. In testing, the system captured around 90% of frauds amongst highest-risk transactions while reducing false positives by more than 80%. Dell Technologies has doubled its high-risk fraud capture rates and reduced manual reviews of low-risk transactions by 83% since implementing the solution. The launch addresses rising fraud costs, with one in every 11 new account creations globally being fraudulent attempts, according to LexisNexis's Cybercrime Report 2026. The solution analyses email, IP, phone and address signals whilst providing transparent scoring with clear reason codes for each risk assessment.
LexisNexis Risk Solutions and IMS have integrated the LexisNexis Drive Metrics scoring model into the IMS EdgeSDK to create a smartphone-based telematics solution for US auto insurers. The integration enables insurers to launch or improve usage-based insurance programmes whilst reducing costs by 50% or more by eliminating cloud processing and storage fees. The solution keeps driving behaviour data on users' devices whilst generating scores that can be incorporated into existing workflows. It can be embedded into insurance company apps or utilised through an IMS white-label app. The LexisNexis Drive Metrics model has demonstrated 79% improvement above standard rating factors. The partnership aims to make telematics intelligence accessible to insurers of all sizes, providing more personalised pricing for consumers whilst maintaining data privacy and transparency.
Arizona has launched the nation's first Digital Birth Credential in collaboration with LexisNexis Risk Solutions and state agencies. The programme allows Arizona-born residents to access a verified digital version of their birth certificate on their mobile devices. Residents can present the credential from their smartphones when applying for services at Arizona Department of Transportation Motor Vehicle Division offices. The initiative aims to reduce reliance on paper documents whilst lowering risks of document loss, theft, and identity fraud. The programme initially launched at three MVD pilot locations in November 2025 before expanding statewide on 1 June 2026. It leverages LexisNexis VitalChek technology to streamline workflows and enhance fraud prevention, establishing a model for digital government transformation nationwide.
LexisNexis Risk Solutions has launched Location Intelligence for Home, an AI-driven predictive model for US home insurance carriers to assess property risk. The tool uses neural network modelling and industry-wide claims data to evaluate six perils, including hail, wind and non-weather water damage. Properties with the highest Location Intelligence scores are 20 times more likely to have a claim than those with the lowest scores. The system addresses gaps in traditional assessment methods, particularly important as non-weather water claims represented 24% of all claims in 2025. The solution integrates within LexisNexis Smart Selection, enabling underwriters to apply location-based insights consistently across new business and renewals. The company plans to file the model in various US states for underwriting and rating workflows.
Cytora and LexisNexis Risk Solutions have announced a strategic partnership to enhance digital risk processing for US commercial insurers by integrating LexisNexis data and analytics into Cytora's AI-powered underwriting platform. The collaboration allows commercial insurers to automatically enrich submissions with external information, reducing manual lookups and accelerating risk decisioning. Cytora's platform digitises incoming risks and augments them with external data sources, whilst LexisNexis provides industry-leading data analytics and proprietary linking technology for business entity resolution. The integration begins with US commercial business firmographics data via LexisNexis Commercial Data Prefill, with additional LexisNexis commercial insurance products to follow. The partnership aims to transform underwriting from a reactive process into a proactive, insight-driven discipline whilst streamlining critical processes across the entire policy lifecycle.