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Mlops Data Engineer Jobs in Rhode Island (NOW HIRING)

Collaborate with data engineers, analysts, and business stakeholders to integrate data, services ... Understanding of cloud-native architecture and AI/MLOps practices, especially in Azure; basic ...

Collaborate with data engineers, analysts, and business stakeholders to integrate data, services ... Understanding of cloud-native architecture and AI/MLOps practices, especially in Azure; basic ...

Lead AI Application Security Engineer

NC · On-site +1

$59 - $78.75/hr

Partner with application, cloud, infrastructure, data engineering, and Information Security teams ... Knowledge of EU AI Act requirements, AI governance, model lifecycle security, MLOps/LLMOps, Lean ...

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Mlops Data Engineer information

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

What are the key skills and qualifications needed to thrive as an MLOps data engineer?

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What are popular job titles related to Mlops Data Engineer jobs in Rhode Island?

For Mlops Data Engineer jobs in Rhode Island, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Rhode Island look for?

The top searched job categories for Mlops Data Engineer jobs in Rhode Island are:

What cities in Rhode Island are hiring for Mlops Data Engineer jobs?

Cities in Rhode Island with the most Mlops Data Engineer job openings:

AI Platform Director - Data Engineering

First Citizens Bank

Carolina, RI • On-site, Remote

$254K/yr

Full-time

Re-posted 14 days ago


First Citizens Bank rating

7.4

Company rating: 7.4 out of 10

Based on 106 frontline employees who took The Breakroom Quiz

107th of 174 rated banks


Job description

Overview

This is a remote role that may only be hired in the following location(s): North Carolina or Arizona

We are seeking an experienced Director to lead the AI platform engineering and enablement functions within our expanding Cloud Data and AI Platform organization. This role is instrumental in building, operationalizing, and governing the next-generation AI and machine learning ecosystem that powers advanced analytics and responsible AI adoption across the bank. You will own the end-to-end AI lifecycle—from data and model development to MLOps, deployment, governance, and responsible AI compliance in a regulated financial environment.

As a seasoned technology leader, you will bring your expertise in enterprise AI architecture, model operations, and platform engineering to partner with key business, technology, and governance stakeholders—ensuring AI initiatives are responsibly implemented, well-controlled, and deliver measurable value. 


Responsibilities & Qualifications

AWS AI/ML Platform Ownership

  • Architect and lead AI/ML workloads on AWS including:
    • Amazon SageMaker (training, deployment, model registry)
    • AWS Bedrock (foundation models and GenAI use cases)
    • AWS Lambda, ECS, EKS for model serving
    • S3, Glue, Snowflake for data pipelines
  • Define enterprise standards for MLOps, feature stores, and model lifecycle management
  • Build and maintain integrations with enterprise platforms for data ingestion, metadata management, tokenization, and control evidence generation. 
  • Continuously enhance the platform’s automation, resilience, and observability, ensuring robust end-to-end telemetry for both model and data pipelines. 
  • Collaborate with Enterprise Risk, Legal, Compliance, and Model Risk partners to embed Responsible AI principles and audit-ready control evidence directly into platform design. 

Machine Learning & GenAI Execution

  • Oversee development of ML models across all business units including Fraud detection systems, Credit scoring and risk modeling, Customer segmentation and personalization, Liquidity related modeling etc.
  • Lead GenAI initiatives using LLMs for Document intelligence, AI copilots etc.

 

Data & Engineering Collaboration

  • Partner with data engineering teams to ensure high-quality, governed datasets
  • Define feature engineering and data product standards in Snowflake / data lake environments
  • Integrate real-time streaming data for low-latency decision systems

 

Model Governance & Risk Compliance

  • Define and enforce standards, patterns, and guardrails for model deployment, explainability, lineage, and monitoring in alignment with enterprise risk, compliance, and security frameworks. 
  • Partner closely with leaders across Responsible AI Governance, AI Portfolio Management, AI Fluency & Engagement, and Applied Data Science & GenAI, in collaboration with enterprise risk partners, to implement a responsible AI framework that embeds audit-ready control evidence and governance mechanisms directly into the platform’s core design to ensure the platform supports scalable, ethical, compliant, and high-impact AI delivery. 
  • Implement model explainability (SHAP, LIME, interpretability frameworks)
  • Establish responsible AI policies (bias detection, fairness, auditability)

 

Team Building & Leadership

  • Develop and mentor engineering talent, championing Agile practices, continuous learning, and adoption of emerging AI and data engineering technologies. 
  • Mentor senior technical leaders and establish engineering best practices
  • Oversee technical due diligence, onboarding, and management of strategic AI and GenAI vendors and tools, ensuring compatibility with enterprise architecture and control.

Bachelor's Degree and 8 years of experience in Information Technology including application development, support roles, and management.

OR

High School Diploma or GED and 12 years of experience in Information Technology including application development, support roles, and management.

Qualifications

  • Deep hands-on experience building production ML systems on AWS
  • 2+ years in AI/ML, data science, or data engineering leadership roles
  • Strong knowledge of:
    • Machine learning (XGBoost, deep learning, NLP, time series)
    • MLOps practices (CI/CD, model monitoring, drift detection)
    • Distributed systems and cloud architecture
  • Strong programming background in Python + SQL (Scala/Java a plus)
  • Experience working in regulated environments with model governance

Preferred Qualifications

  • Experience with Generative AI / LLM platforms (Bedrock, OpenAI, Claude APIs)
  • Experience in financial services, banking, fintech, or insurance
  • Familiarity with data platforms like Snowflake, Databricks

#LI-JM1


Additional Information

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Qualifications:

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Education:UNAVAILABLEEmployment Type: FULL_TIME

What First Citizens Bank employees say

Pay

Benefits

Hours and flexibility

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