

SeerSolutionsInc
MLOps Engineer : Baltimore, MD
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer in Baltimore, MD, lasting over 2 years, with a pay rate of “”. Key skills include Python, AWS/Azure, CI/CD, and database management. A Bachelor’s degree in a related field is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 4, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Baltimore, MD
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🧠 - Skills detailed
#SageMaker #Data Ingestion #DevOps #ML (Machine Learning) #Deployment #GitHub #AWS (Amazon Web Services) #Data Science #Version Control #Computer Science #NoSQL #MySQL #Cloud #Automation #AWS SageMaker #Monitoring #MongoDB #Scripting #TensorFlow #Python #Azure #PostgreSQL #GIT #Jenkins #PyTorch #Databases #Scala #Data Engineering
Role description
Job Title/Role: MLOps Engineer
Location: Baltimore, MD (5 days on-site, local candidates preferred)
Duration: 2+ Years
Description:
We are seeking an experienced MLOps Engineer to support the deployment, monitoring, and optimization of machine learning systems in production environments. The role involves building and maintaining ML pipelines, automating workflows, managing infrastructure, and collaborating with data science and engineering teams to ensure reliable model performance.
Responsibilities & Qualifications
· Design, build, and manage end-to-end ML pipelines, including data ingestion, preprocessing, model training, validation, and deployment.
· Integrate ML models into production environments using containerization and cloud platforms such as AWS or Azure.
· Implement monitoring and alerting systems to track model performance and system health.
· Automate repetitive tasks within the ML lifecycle to improve reliability and reduce manual effort.
· Optimize the performance and scalability of machine learning models and related infrastructure.
· Collaborate with data scientists and engineers to align MLOps processes with business and technical requirements.
· Maintain and manage cloud-based infrastructure for ML workloads using services like AWS Sagemaker, Azure ML, or equivalent.
· Experience with CI/CD pipelines, version control systems (Git), and DevOps tools (Jenkins, GitHub Actions, etc.).
· Proficient in Python for automation, scripting, and integration with ML frameworks (TensorFlow, PyTorch, scikit-learn).
· Strong understanding of both NoSQL (e.g., MongoDB) and relational databases (e.g., PostgreSQL, MySQL).Solid background in machine learning concepts, model serving, and MLOps best practices.
· Bachelor’s degree in computer science, Data Engineering, or a related field preferred.
· Must be eligible to obtain and maintain a Public Trust clearance
Job Title/Role: MLOps Engineer
Location: Baltimore, MD (5 days on-site, local candidates preferred)
Duration: 2+ Years
Description:
We are seeking an experienced MLOps Engineer to support the deployment, monitoring, and optimization of machine learning systems in production environments. The role involves building and maintaining ML pipelines, automating workflows, managing infrastructure, and collaborating with data science and engineering teams to ensure reliable model performance.
Responsibilities & Qualifications
· Design, build, and manage end-to-end ML pipelines, including data ingestion, preprocessing, model training, validation, and deployment.
· Integrate ML models into production environments using containerization and cloud platforms such as AWS or Azure.
· Implement monitoring and alerting systems to track model performance and system health.
· Automate repetitive tasks within the ML lifecycle to improve reliability and reduce manual effort.
· Optimize the performance and scalability of machine learning models and related infrastructure.
· Collaborate with data scientists and engineers to align MLOps processes with business and technical requirements.
· Maintain and manage cloud-based infrastructure for ML workloads using services like AWS Sagemaker, Azure ML, or equivalent.
· Experience with CI/CD pipelines, version control systems (Git), and DevOps tools (Jenkins, GitHub Actions, etc.).
· Proficient in Python for automation, scripting, and integration with ML frameworks (TensorFlow, PyTorch, scikit-learn).
· Strong understanding of both NoSQL (e.g., MongoDB) and relational databases (e.g., PostgreSQL, MySQL).Solid background in machine learning concepts, model serving, and MLOps best practices.
· Bachelor’s degree in computer science, Data Engineering, or a related field preferred.
· Must be eligible to obtain and maintain a Public Trust clearance






