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Senior Machine Learning Ops Engineer Jobs in Pennsylvania

RELX

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

As a Senior Machine Learning Ops Engineer, you will bridge Data Science and Engineering to develop AI-based features and ensure the reliability and scalability of machine learning models and services.

Elsevier

Senior ML Ops Engineer

Philadelphia, PA

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global ... About the role, as a Senior Machine Learning Engineer you'll work onAI-based features (GenAI ...

RELX Group plc

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global ... About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI ...

RELX

Senior ML Ops Engineer

Philadelphia, PA

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global ... About the role, as a Senior Machine Learning Engineer you'll work onAI-based features (GenAI ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global ... About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI ...

BE Group

Senior Machine Learning Engineer

Malvern, PA · On-site

$120K - $158K/yr

We are assisting our client in hiring for a Senior Machine Learning Engineer. Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps ...

System One

Sr Machine Learning Engineer

Pittsburgh, PA · On-site

$101K - $139K/yr

Position Title: Sr Machine Learning Engineer Location: PA - Pittsburgh, TX - Dallas, OH - Cleveland Work Status : Onsite 5 days a week Duration : Contract to Hire Years Of Experience Required : 10+ ...

Vanguard Group

Senior Machine Learning Engineer

Malvern, PA · On-site

$102K - $140K/yr

Design, build, and maintain end-to-end machine learning pipelines from research through production deployment. * Engineer scalable training, inference, and retraining workflows using AWS SageMaker.

Vangard, Inc.

Senior Machine Learning Engineer

Malvern, PA

$102K - $140K/yr

Design, build, and maintain end-to-end machine learning pipelines from research through production deployment. * Engineer scalable training, inference, and retraining workflows using AWS SageMaker.

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... engineers Qualifications * U.S. Citizenship is required * Advanced degree, or bachelor's with at least 3 years of experience, in Data Science, Machine Learning or a related field Required Skills:

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... engineers Qualifications * U.S. Citizenship is required * Advanced degree, or bachelor's with at least 3 years of experience, in Data Science, Machine Learning or a related field Required Skills:

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... engineers Qualifications * U.S. Citizenship is required * Advanced degree, or bachelor's with at least 3 years of experience, in Data Science, Machine Learning or a related field Required Skills:

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Senior Machine Learning Ops Engineer information

What are the key skills and qualifications needed to thrive as a senior machine learning ops engineer?

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges faced by senior machine learning ops engineers when deploying models to production?

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

What is the difference between Senior Machine Learning Ops Engineer vs Data Engineer?

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

What is a senior machine learning ops engineer?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.

What are popular job titles related to Senior Machine Learning Ops Engineer jobs in Pennsylvania?

For Senior Machine Learning Ops Engineer jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Ops Engineer jobs in Pennsylvania look for?

The top searched job categories for Senior Machine Learning Ops Engineer jobs in Pennsylvania are:

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Cities in Pennsylvania with the most Senior Machine Learning Ops Engineer job openings:

Senior Machine Learning Ops Engineer jobs near you

Senior ML Ops Engineer

RELX

Philadelphia, PA • On-site

$99K - $137K/yr

Full-time

Re-posted 5 days ago

Job description

Job Summary:
Elsevier Inc. is a renowned global information analytics company focused on providing scientific, technical, and medical research content. As a Senior Machine Learning Ops Engineer, you will bridge Data Science and Engineering to develop AI-based features and ensure the reliability and scalability of machine learning models and services.
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.
Qualifications:
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.
Company:
RELX is a provider of information-based analytics for professional and business customs. Founded in 1993, the company is headquartered in London, GBR, with a team of 1001-5000 employees. The company is currently Late Stage.

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