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Machine Learning Engineer Opt Jobs in Rhode Island

Data Engineer II

Providence, RI · On-site

$115K - $138K/yr

About the Role We are seeking a Data Engineer II to join our Global Data Platform & Engineering ... Exposure to AI/ML workflows or data preparation for machine learning and generative AI applications.

Data Engineer II

Providence, RI · On-site

$115K - $138K/yr

About the Role We are seeking a Data Engineer II to join our Global Data Platform & Engineering ... Exposure to AI/ML workflows or data preparation for machine learning and generative AI applications.

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Machine Learning Engineer Opt information

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What are popular job titles related to Machine Learning Engineer Opt jobs in Rhode Island? For Machine Learning Engineer Opt jobs in Rhode Island, the most frequently searched job titles are:
What cities in Rhode Island are hiring for Machine Learning Engineer Opt jobs? Cities in Rhode Island with the most Machine Learning Engineer Opt job openings:
Principal Data Engineer - Neo4J

Principal Data Engineer - Neo4J

Citizens

Johnston, RI

Other

Posted 21 days ago


Job description

Description

Principal Data Engineer - Graph Data Engineering Neo4j

Role Summary

As Principal Data Engineer, you will be chartered with developing functional systems to realize key business objectives and goals, with a specialization in graph data engineering and connected data architecture. You will help lead a team of data engineers as you create interfaces, graph models, and data platforms that facilitate the flow, linkage, and contextualization of information across Citizens' business operations.

In this role, you will establish and scale graph-based solutions using Neo4j, enabling relationship-driven insights, network analytics, and advanced data discovery across domains such as fraud detection, risk analysis, and customer intelligence.

Specialized Responsibilities

  • Serve as a key contributor in designing and delivering graph data solutions, partnering with stakeholders to translate business needs into connected data models and graph architectures
  • Engineer and maintain graph database Neo4j, alongside relational and non-relational systems to support hybrid data environments
  • Develop and operationalize relationship-based data models, including nodes, edges, and properties aligned to enterprise business domains
  • Design and implement knowledge graphs and connected data platforms that unify disparate data sources and expose relationships across systems
  • Build and optimize graph ingestion pipelines for batch and streaming data sources, ensuring data freshness and integrity
  • Develop mechanisms and architectures that support business line specific use cases
  • Establish standards and best practices for graph modeling, schema evolution, and governance within the enterprise data ecosystem
  • Review and manage interfaces supporting graph data access including APIs, visualization tools, and analytics platforms
  • Partner with data science and analytics teams to enable graph-based feature engineering and machine learning integration

Preferred Technical Expertise

  • Deep expertise in Neo4j platform capabilities, including clustering, security, and enterprise deployment patterns
  • Experience in graph data modeling and ontology design for complex enterprise datasets
  • Knowledge of connected data architecture patterns, including knowledge graphs and data fabrics
  • Experience integrating graph platforms with big data ecosystems (Spark, Kafka, etc.) and cloud-native services
  • Strong understanding of query optimization, indexing, and graph performance tuning
  • Experience with data ingestion frameworks supporting both batch and real-time pipelines
  • Proficiency in Python

Business Outcomes and Impacts

  • Enable enhanced fraud detection and prevention through network-based analysis of entities, transactions, and behaviors
  • Accelerate Customer 360 insights by linking fragmented data across business domains
  • Support real-time decisioning through connected data models and optimized graph queries
  • Drive improved data integrity and lineage visibility through network-based representations
  • Enable faster, more scalable delivery of insight-driven business capabilities through reusable graph models

Preferred Qualifications

  • 8+ years of experience in data engineering, including experience leading engineers and technical teams
  • Proven experience implementing Neo4j in enterprise environments
  • Familiarity with machine learning and AI techniques leveraging graph data
  • Experience working in Agile environments and leading cross-functional delivery teams
  • Experience with visualization and BI tools in conjunction with graph-derived insights

Modernization and Architecture Expectations

  • Advance the organization's data architecture toward connected, relationship-driven models, complementing existing data platforms
  • Establish graph-first design patterns where relationship complexity drives business value
  • Integrate Neo4j into the broader enterprise data ecosystem (cloud, lakehouse, streaming platforms)
  • Promote adoption of knowledge graphs and semantic modeling to improve interoperability and reuse
  • Implement scalable, resilient graph data platforms aligned to enterprise security and compliance standards
  • Standardized graph engineering practices, including modeling guidelines, performance tuning, and operational monitoring
  • Partner with architecture leadership to define the future-state connected data vision, ensuring alignment with digital and AI strategies

Some job boards have started using jobseeker-reported data to estimate salary ranges for roles. If you apply and qualify for this role, a recruiter will discuss accurate pay guidance.

Equal Employment Opportunity

Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.

Education:Why Work for UsEmployment Type: 1ST