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Mlops Data Engineer Jobs (NOW HIRING)

Whisker

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Develops and supports MLOps workflows, including model tracking, versioning, and lifecycle management using MLflow * Builds and maintains CI/CD pipelines for both data engineering and machine ...

Vings Technologies

Data Engineer

San Jose, CA · On-site

$134K - $161K/yr

... MLOps pipelines for data preprocessing, feature engineering, model training, validation, and ... deployment using tools like Vertex AI, BigQuery. etc. · Conduct deep data analysis to uncover ...

MedReview

Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

MLOps Integration: Collaborate with Data Scientists to implement automated CI/CD pipelines for ... ML Engineering: Familiarity with ML frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow ...

MedReview

Data Engineer

Manhattan, NY · Remote

$105K - $115K/yr

MLOps Integration: Collaborate with Data Scientists to implement automated CI/CD pipelines for ... ML Engineering: Familiarity with ML frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow ...

Accenture Federal Services

Data Engineer

Suitland, MD

$123K - $148K/yr

Data Engineer We are looking for a skilled and passionate Data Engineer to join our team. You will ... ML Integration / MLOps : Support the implementation, deployment, and scaling of machine learning ...

airSlate Inc.

$105K - $126K/yr

A Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a ... Experience contributing to MLOps workflows and CI/CD for ML models. * Exposure to A/B testing ...

TEKsystems

Data Engineer

Durham, NC · Remote

$150K/yr

Support and enhance enterprise MLOps capabilities and machine learning pipelines. * Enable ... Deep understanding of data engineering concepts, including: Data lakes Data pipelines Data ...

Alpha Consulting Corp.

Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Alpha Consulting Corp. is seeking a highly skilled MLOps Engineer / Python Developer with expertise in building and maintaining scalable data and machine learning pipelines. The role involves ...

Qualysoft

Erwartungsmanagement Anforderungen Mehrjahrige Erfahrung als MLOps Engineer, ML Engineer oder Data ... Engineer Sehr gute Kenntnisse in Kubernetes-/OpenShift-basierten Umgebungen Erfahrung mit ML ...

ClifyX

Python AI/GenAI developer

Denver, CO · On-site

$51.75 - $71.25/hr

... AI/GenAI developer. The role involves working with Google technologies, local LLMs, vector ... MLOps data models. Responsibilities : • Exposure to Google technologies - Google ADK, Google ...

Berkley

Databricks Data Engineer

Manassas, VA · On-site

$114K - $137K/yr

MLOps & ML-Enabled Data Pipelines * Partner with data scientists and data engineers to create feature pipelines, model training pipelines, and production scoring pipelines. * Deploy and ...

SOSi

Data Engineer

Redstone Arsenal, AL · On-site

$116K - $140K/yr

Overview SOS International LLC (SOSi) is seeking Data Engineers to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government ...

SOSi

Data Engineer

Redstone Arsenal, AL · On-site

$116K - $140K/yr

Overview SOS International LLC (SOSi) is seeking Data Engineers to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government ...

Travelers

Data Engineer II - MLOps Engineer

Hartford, CT · On-site

$126K - $208K/yr

As a Data Engineer II on this team, you turn ML from a promising notebook into a reliable product ... Build, deploy, and support ML pipelines in a modern MLOps environment, partnering closely with data ...

E-Solutions, Inc.

Data Engineer - AI/ML

San Jose, CA · On-site

Data Engineer - AI/ML Location: San Jose, CA Duration: 12+ Month Long-Term Contract -W2 GC-EAD,TN ... MLOps: Solid understanding of MLOps principles and experience with related tools (e.g., Vertex AI ...

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Showing results 21-40

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Mlops Data Engineer information

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$129.7K

$177.5K

How much do mlops data engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for mlops data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

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.
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Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer

Auburn Hills, MI • On-site

Whisker
See more jobs at Whiskerexternal

$108K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.

Whisker rating

7.7

Company rating: 7.7 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

Whisker is redefining what it means to live with cats-designing intelligent systems that remove friction, elevate the everyday, and celebrate the quiet brilliance of feline companionship. Today, Litter-Robot leads the category. Tomorrow, an entire ecosystem that expands what's possible for cats and the people who love them. We believe the future is feline. And we're imagining that future today.
We work onsite 4+ days a week, with our team based in Auburn Hills, Michigan, and Juneau, Wisconsin. Our team of 700+ passionate pet people thrives on collaboration, innovation, and the occasional office cameo from a four-legged friend.
What You'll Do:
We are seeking a Senior Data Engineer / Data Engineer with strong hands-on Databricks experience to design, build, and optimize scalable data pipelines and platforms that power analytics and decision-making across the organization. This role partners closely with data science, analytics, and engineering teams to deliver reliable, high-performance data solutions in a modern cloud lakehouse environment.
Summary:
The Senior Data Engineer / Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines and infrastructure using Databricks and related cloud technologies. This role ensures data is reliable, secure, and readily accessible to support analytics, reporting, and machine learning initiatives.
Essential Duties and Responsibilities
  • Designs, builds and maintains scalable ETL/ELT pipelines using Databricks, Apache Spark, and Delta Lake
  • Develops and optimizes data workflows for batch and streaming data processing
  • Architects and implements data lakehouse solutions following medallion architecture (bronze/silver/gold layers using DBT)
  • Collaborates with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions
  • Writes efficient, well-documented PySpark/SQL code for data transformation and processing
  • Develops and supports MLOps workflows, including model tracking, versioning, and lifecycle management using MLflow
  • Builds and maintains CI/CD pipelines for both data engineering and machine learning model deployment
  • Implements monitoring and alerting for data pipelines and ML models to proactively identify and troubleshoot performance issues, data drift, and failures
  • Monitors, troubleshoots, and optimizes pipeline and model performance, resource utilization, and cost efficiency within Databricks
  • Ensures data quality, integrity, and governance across all pipelines and datasets
  • Manages and optimizes Databricks clusters, jobs, and workflows
  • Integrates Databricks with cloud platforms (Azure, AWS, or GCP) and other enterprise systems
  • Implements data security best practices, including access controls and data masking
  • Mentors junior data engineers and provide technical guidance on best practices, including MLOps standards
  • Participates in architecture reviews and contribute to the evolution of the data and ML platform strategy
  • Documents technical designs, data models, pipeline processes, and ML deployment workflows
  • Stays current with emerging tools, technologies, and best practices in data engineering and MLOps
  • Performs additional responsibilities when required

Requirements
What You'll Bring:
  • BA/BS in Computer Science, Software Engineering, or a related technical field, and/or equivalent years of experience
  • 8+ years of professional software engineering experience, including 3+ years directly managing engineers with ownership of hiring, performance, and career development
  • Demonstrated success leading backend service teams at consumer scale with distributed services and APIs supporting a large installed base of application users or devices
  • Expertise in API design and service architecture, including versioning and backward compatibility for clients that cannot all be upgraded at once
  • Experience with high-volume data ingestion and event-driven architecture (Kafka, Kinesis, or equivalent), including the pipelines that feed analytics and machine learning
  • A track record of driving measurable reliability improvement - fewer or less severe incidents, improved uptime, a healthier on-call practice, or materially more stable deployments
  • Experience leading distributed teams across multiple time zones, including blended teams of full-time employees and contractors or outsourced partners
  • Experience inheriting an existing team and improving retention, role clarity, and delivery predictability
  • Proven ability to recruit, level, and develop engineers, including promoting individual contributors into senior and lead roles
  • Current technical credibility: able to review code, lead architecture discussions, and prototype solutions independently.
  • Working experience with AWS infrastructure and the ability to own cloud architecture, cost, and capacity decisions for the services their team runs.
  • Familiarity with platform engineering practice such as infrastructure as code, CI/CD pipelines, containerization or serverless deployment models, and observability tooling sufficient to set direction and hold quality standards
  • Ability to work a hybrid schedule based out of Whisker's Auburn Hills, Michigan headquarters
  • Maintains confidentiality of proprietary information
  • Ability to maintain a professional atmosphere in a fast-paced environment with numerous interactions and interruptions
  • A high degree of initiative, self-motivation, and ability to motivate others
  • Ability to establish and maintain cooperative working relationships with Team Members and colleagues
  • Comfortable with office pets (cats, dogs)

Not Required but Nice to Have!
  • Strongly preferred experience with IoT or connected-device platforms, device telemetry, fleet management, over-the-air updates, MQTT or similar protocols
  • Background at a consumer hardware or connected-product company where software ships alongside physical product
  • Experience managing the firmware-to-cloud boundary and hardware-dependent release trains, including field failure analysis
  • Deeper platform or SRE background such as Kubernetes, ECS, Terraform, or equivalent at production scale
  • Experience with GraphQL and API gateway patterns
  • Experience with time-series or purpose-built IoT data stores
  • Experience transitioning a contractor-heavy team toward a stronger full-time core without disrupting delivery
  • Experience in a direct-to-consumer or subscription business
  • Prior Director of Engineering experience is welcome - this role owns a broad scope across several service domains

Benefits & Purrks:
Join a tenacious, inventive company that empowers team members to chart their own path, lead by grounding decisions in the "why", and has a strong sense of empathy and openness to new perspectives. Be a part of exciting growth, work with incredible people, and create tomorrow's pet products-plus a whole lot of extras. You will also be provided with:
  • Premium Medical/Dental/Vision insurance
  • Paid parental leave
  • Whisker Parents Program
  • 1 day "pawternity" leave for new pet adoption
  • Pet Insurance Discount
  • 401K match
  • Flexible spending accounts
  • Company-paid short-term disability and life insurance
  • Employee Assistance Program (EAP)
  • Generous paid time off
  • 14 Paid Holidays
  • Top of the line equipment
  • Pet-friendly office
  • Whisker products and swag
  • Continuing education Support
  • On-site gym with Peloton
  • Referral program

Statement of Inclusivity:
We believe different perspectives make Whisker better and strive to create a place where everyone has equal opportunities to thrive.
Please ensure to regularly check your email spam folder for any communication from Whisker to avoid missing important updates regarding your application status.

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