Senior ML Ops Engineer
Location
Connecticut + 3 moreAll locations: Connecticut | New Jersey | Pennsylvania | Virginia
Posted
52 days ago
Salary
$95.3K - $158.8K / year
Seniority
Senior
Job Description
Senior ML Ops Engineer
RELX
• 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.
Job Requirements
- 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
- Background in health technology and/or medical content workflows 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.
Benefits
- This job is eligible for an annual incentive bonus
- We are delighted to offer country specific benefits.
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