Senior ML Ops Engineer

Elsevier; Philadelphia (Philadelphia County); On-site; USD 95,000 - 159,000; Full time

Benefits offered by this job

Country-specific benefits

Job summary

Elsevier is seeking a Senior Machine Learning Engineer to bridge Data Science and Engineering for secure, scalable AI services powering Clinical Key AI, Sherpath AI, and knowledge workflows. You’ll work on GenAI, RAG, and retrieval systems, building end-to-end ML pipelines and governance across major cloud platforms.

You will collaborate with data scientists and product teams to translate problems into production-grade ML solutions, with emphasis on responsible AI, model evaluation, and scalable

Qualifications

• Production ML or GenAI systems experience.
• Proficiency in Python/Java/Scala.
• Cloud experience with AWS/Azure/Google.
• Experience with search, vector, and graph tech.
• Experience evaluating LL models.
• Understanding of DS lifecycle, feature engineering, and evaluation metrics.
• Background in health tech/workflows preferred.
• Familiarity with PyTorch, TensorFlow, PySpark.
• Experience with large-scale data processing (Spark).
• Knowledge of NLP and ML theory.

Responsibilities

• Automate and orchestrate ML workflows across cloud platforms.
• Maintain and version model registries and artifacts.
• Develop and manage ML CI/CD, data validation, and deployment.
• Implement ML solutions with MLOps platforms (SageMaker, MLflow, Azure ML).
• Scale end-to-end Sagemaker pipelines.
• Design GAR+RAG systems and manage prompts/guardrails.
• Design ML pipelines using Elasticsearch/OpenSearch/Solr, vector/graph DBs.
• Build evaluation pipelines (IR metrics, LLM quality metrics) and AB tests.
• Optimize infrastructure costs and resource utilization.
• Stay updated with GAI/NLP/RAG research and apply advances.

Skills

ML Engineering

MLOps platforms

Python/Java/Scala

Cloud platforms

Search/Vector/Graph

LLM evaluation

Data Science life cycle

Health tech background

ML frameworks

Spark/NLP

Tools

Elasticsearch/OpenSearch/Solr

Neo4j

MLflow

SageMaker/Bedrock

Job description

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization?

Are you looking to drive cutting edge products that have a true societal impact?

About the team, this team that powers Elsevier’s Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models intosecure, reliable, and scalableservices. Our systems operate over one of the world’s largest medical and scholarly landscapes.

About the role, as a Senior Machine Learning Engineer you’ll work onAI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrievalwhile enforcingcontent rights and editorial confidentiality.

Key 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 manageCI/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), manageprompt libraries,guardrailsandstructured outputfor LLMs hosted onBedrock/SageMakeror self-hosted.
• Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs.
• Buildevaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), andA/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.

Collaboration

• 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.

Qualifications

• Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production.
• StrongPython, Java, and/or Scalaexperience 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.
• Background in health technology and/or medical contentworkflows is preferred.
• 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.

Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer‑reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields.

U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates.If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826.This job is eligible for an annual incentive bonus.

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