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Mlops Data Engineer Jobs in Alabama (NOW HIRING)

SOSi

Software Developer

Redstone Arsenal, AL

Implement and manage data workflows using Apache Airflow and Kafka. * Automate the training ... MLOps, DevOps, or related roles. * Proficiency in Python and experience with its frameworks.

SOSi

Software Developer

Redstone Arsenal, AL · On-site

Implement and manage data workflows using Apache Airflow and Kafka. * Automate the training ... MLOps, DevOps, or related roles. * Proficiency in Python and experience with its frameworks.

Ag

Lead AI Solutions Systems Engineer

Mobile, AL · On-site

Evaluate the technical feasibility, data readiness, and infrastructural viability of proposed AI ... MLOps release pipelines * Lead and frame assistant/agent coding practices across the team and its ...

IGNITE

AI PIPELINE ENGINEER

Huntsville, AL · On-site

Responsibilities : • Design and implement AI pipelines for data ingestion, processing, and model ... MLOps practices for continuous integration and deployment of AI models. • Strong written and ...

IGNITE

AI PIPELINE ENGINEER

Huntsville, AL · On-site

... data ingestion, processing, and model deployment using frameworks like LangChain and Open WebUI ... MLOps practices for continuous integration and deployment of AI models. • Strong written and ...

Deloitte

AI Security Engineer Manager

Huntsville, AL · On-site

As a Manager in AI Security Engineering, you will play a critical role in securing the development ... data protection, access control, model validation, and monitoring within DevSecOps and MLOps ...

Deloitte

AI Security Engineer Manager

Birmingham, AL · On-site

As a Manager in AI Security Engineering, you will play a critical role in securing the development ... data protection, access control, model validation, and monitoring within DevSecOps and MLOps ...

1st Edge LLC

2026-01-1E AI/ML Engineer

Huntsville, AL · On-site

Collaborate with data scientists, software engineers, and integrated product team stakeholders to ... Experience working with MLOps for experiment tracking and model deployment * Strong proficiency in ...

New

1st Edge, LLC

2026-01-1E AI/ML Engineer

Huntsville, AL · On-site

Collaborate with data scientists, software engineers, and integrated product team stakeholders to ... Experience working with MLOps for experiment tracking and model deployment * Strong proficiency in ...

New

1st Edge, LLC

2026-01-1E AI/ML Engineer

Huntsville, AL · On-site

Collaborate with data scientists, software engineers, and integrated product team stakeholders to ... Experience working with MLOps for experiment tracking and model deployment * Strong proficiency in ...

New

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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 Alabama?

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

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

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

What cities in Alabama are hiring for Mlops Data Engineer jobs?

Cities in Alabama with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you

Software Developer

SOSi

Redstone Arsenal, AL

Full-time

Re-posted 6 days ago

Job description

Company Description

Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.

Job Description

Overview

SOS International LLC (SOSi) is seeking highly skilled Software Developers to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in Huntsville, Alabama. This role will be responsible for delivering automation to key national security missions interacting with petabyte-scale data on an HPC. 

In this role, you will play a pivotal role in designing, developing, and maintaining MSIC software applications. You will work closely with cross-functional teams to deliver high-quality solutions that meet our clients' needs. Your expertise in Python, Docker, NoSQL, SQL, and Apache Airflow/Kafka will be crucial in driving our projects forward.

Essential Job Duties

  • Design, develop, test, and maintain software applications using Python.
  • Design, implement, and manage scalable MLOps pipelines and infrastructure.
  • Develop and manage containerized applications using Docker.
  • Work with NoSQL and SQL for database management and optimization.
  • Implement and manage data workflows using Apache Airflow and Kafka.
  • Automate the training, testing, and deployment of machine learning models.
  • Implement and manage APIs and ensure their scalability, reliability, and performance.
  • Implement and manage infrastructure as code and configuration management tools.
  • Collaborate with data scientists to integrate machine learning models into applications.
  • Design and develop microservices architecture for scalability and efficiency.
  • Write clean, scalable, and efficient code.
  • Participate in the entire software development lifecycle, from concept and design to testing and deployment.
  • Troubleshoot, debug, and upgrade existing software.
  • Provides leadership, support and guidance to all AIMS Team Members.
  • Ensures and promotes the development of the AIMS team through coaching, training, and leadership development.
  • Provides informal feedback on an ongoing basis and formal feedback in the annual performance evaluation process to identify and develop talent.
Qualifications

Minimum Requirements

  • Top Secret Security Clearance with SCI eligibility.
  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 2-4 years of experience in software development, MLOps, DevOps, or related roles.
  • Proficiency in Python and experience with its frameworks.
  • Extensive knowledge of containerization and orchestration tools (Docker, Kubernetes).
  • Experience with CI/CD tools (Jenkins, GitLab CI, CircleCI) and automated testing.
  • Experience with version control systems (Git, SVN).
  • Hands-on experience with NoSQL and SQL.
  • Proficient in using Apache Airflow for workflow management.
  • Proficiency with cloud platforms (AWS, Azure, Google Cloud).
  • Solid understanding of software architecture and design patterns.
  • Strong problem-solving skills and attention to detail.
  • Excellent communication and teamwork skills.
  • Ability to work independently and manage multiple tasks efficiently.
  • Experience with agile development methodologies.

Preferred Qualifications

  • Familiarity with event-driven architecture and messaging systems (Kafka, RabbitMQ).
  • Experience with feature stores and model registries.
  • Familiarity with big data technologies (Spark, Hadoop)
  • Knowledge of monitoring and logging tools for machine learning models (Prometheus, Grafana, ELK stack).
  • Significant experience with petabyte scale data sets.
  • Significant experience with large-scale, multi-INT analytics.
Additional Information

Work Environment

  • Working conditions are normal for an office environment.
  • Fast paced, deadline-oriented environment.
  • May require periods of non-traditional working hours including consecutive nights or weekends (if applicable).

Working at SOSi

All interested individuals will receive consideration and will not be discriminated against for any reason.

Apply