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LexisNexis Risk Solutions · 2 days ago

Senior ML Ops Engineer

Home based-Connecticut

Full-time

Onsite

Mid, Senior Level

$95K/yr - $159K/yr

Elsevier Inc. is a renowned global information analytics company focused on providing scientific, technical, and medical research content. The Senior ML Ops Engineer will bridge Data Science and Engineering to develop and manage machine learning workflows, ensuring secure, reliable, and scalable services for AI-based features.

AnalyticsHealth CareInformation TechnologyInsurTechRisk ManagementSoftware

Culture & Values

H1B Sponsor Likely

Responsibilities

Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI)

Maintain and version model registries and artifact stores to ensure reproducibility and governance

Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment

Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML

Scale end-end custom Sagemaker pipelines

Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted

Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs

Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing

Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization

Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems

Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions

Collaborate and interface with Operations Engineers who deploy and run production infrastructure

Qualification

ML EngineeringMLOps platformsCloud solutionsSearch technologiesPythonJavaScalaData Science Life CycleML frameworksLarge-scale data processingStatistical analysisNatural language processingHealth technology

Required

Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production

Strong Python, Java, and/or Scala experience will be considered a plus

Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google)

Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j)

Experience in evaluating LLM models

A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics

Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark

Experience with large-scale data processing systems, e.g., Spark

Experience with statistical analysis, machine learning theory and natural language processing

Preferred

Background in health technology and/or medical content workflows is preferred

Benefits

This job is eligible for an annual incentive bonus.

We are delighted to offer country specific benefits.

Company

LexisNexis Risk Solutions

Glassdoor4.0

LexisNexis Risk Solutions provides information to assist customers in industry and government in assessing, predicting, and managing risk. It is a sub-organization of ChoicePoint.

Founded in 2000

Alpharetta, Georgia, USA

10001+ employees

https://risk.lexisnexis.com

H1B Sponsorship

LexisNexis Risk Solutions has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

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Trends of Total Sponsorships

2025 (129)

2024 (132)

2023 (86)

2022 (98)

2021 (125)

2020 (53)