ZipRecruiter

Log In

1

Mlops Data Engineer Jobs in Rhode Island (NOW HIRING)

Cisco

Applied AI Scientist

Providence, RI

Collaborate with engineering, product, and data science teams to understand requirements ... MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates ...

previous page

Showing results 21-23

All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Rhode Island

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:

Mlops Data Engineer jobs near you

Senior Machine Learning Engineer - Providence - Rag/LLM/Ai

Motion Recruitment Partners, LLC

Providence, RI • On-site

$105K - $145K/yr

Other

Medical, Dental, Vision, Retirement

Posted 24 days ago

Job description


A well-established enterprise information and analytics organization is adding a Senior Machine Learning Engineer to its Providence team. Working on a hybrid schedule, this person will lead technical efforts that turn emerging AI concepts into durable, large-scale product capabilities.
You will focus on intelligent tools built for research-intensive professional users, with an emphasis on generative AI, semantic search, retrieval frameworks, and multi-step agent workflows. The role blends hands-on development with technical leadership: evaluating new approaches, shaping reusable platform patterns, and establishing standards that help AI solutions operate consistently across a global product portfolio.
Required Skills & Experience
Extensive experience designing and delivering applied machine learning solutions
Proven ability to build systems powered by large language models and AI agents
Strong understanding of retrieval-augmented generation, embeddings, and vector-based search
Experience supporting model delivery through MLOps tooling and production practices
Advanced Python programming ability
Experience deploying cloud-native services with AWS and Kubernetes
Desired Skills & Experience
Prior work in legal technology, knowledge management, publishing, or another information-rich industry
12 or more years of software development experience, or at least 8 years plus a doctorate
Degree in computer science, machine learning, engineering, or a comparable technical field
What You Will Be Doing
Daily Responsibilities
100% hands-on technical contribution
Develop and release AI features that improve how professionals discover, evaluate, and use complex information
Create scalable services and shared infrastructure for distributed machine learning applications
Implement retrieval pipelines, agent orchestration, and supporting components for generative AI products
Coordinate with application, cloud, data, and security teams to meet performance, reliability, and governance requirements
The Offer
Performance bonus eligibility
You will receive the following benefits
Medical insurance options
Dental coverage
Vision coverage
Paid time away from work
401(k) plan with company matching when applicable
This opportunity follows a hybrid work model in Providence, Rhode Island.
Applicants must have unrestricted authorization to work in the United States on a full-time basis now and in the future.

Apply