2 days ago
Base Salary
$115k - $192k/yr
Responsibilities
- Automate and orchestrate machine learning workflows across AWS, Azure, Databricks, and foundation model APIs such as OpenAI.
- Maintain model registries and artifact stores and develop CI/CD workflows with data validation, model testing, and deployment automation.
- Build custom SageMaker pipelines for recommendation systems and implement ML engineering solutions using SageMaker, MLflow, and Azure ML.
- Design engineering components for RAG and retrieval systems, including query interpretation, chunking, embeddings, hybrid retrieval, semantic search, prompt libraries, guardrails, and structured LLM output.
- Develop ML pipelines using Elasticsearch, OpenSearch, Solr, vector databases, and graph databases.
- Build evaluation pipelines covering information-retrieval metrics, LLM quality metrics, and A/B testing.
- Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization.
- Collaborate with subject-matter experts, product managers, data scientists, Responsible AI experts, and operations engineers.
Requirements
- 3–5+ years of experience in ML Engineering, MLOps platforms, or shipping ML, search, or GenAI systems to production.
- Strong Python, Java, and/or Scala engineering experience.
- Experience with statistical analysis, machine learning theory, and natural language processing.
- Hands-on experience with major cloud vendors, including AWS, Azure, and/or Google.
- Experience with search, vector, and graph technologies such as Elasticsearch, OpenSearch, Solr, and Neo4j.
- Experience evaluating LLM models.
- Background with scholarly publishing workflows, bibliometrics, or citation graphs.
- Strong understanding of the data science lifecycle, including feature engineering, model training, and evaluation metrics.
- Familiarity with PyTorch, TensorFlow, PySpark, and large-scale data processing systems such as Spark.
Benefits
- Flexible working hours.
- Wellbeing initiatives.
- Shared parental leave.
- Study assistance.
- Sabbaticals.
- Role locations are Philadelphia, USA, or Mexico City, Mexico.
Tech Stack
Categories
About Elsevier
Elsevier builds scientific and medical information products and analytics platforms for researchers, clinicians, and educators. Its portfolio includes journals and databases such as The Lancet, Cell, ScienceDirect, Scopus, and ClinicalKey, sold primarily via institutional subscriptions, licensing, and open-access publishing fees. Founded in 1880 and headquartered in Amsterdam, Elsevier operates as a business of RELX, serving universities, hospitals, corporations, and government research agencies worldwide.