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MLOps Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer on a 12-month contract in Sunnyvale, CA, requiring 3 days onsite and 2 days remote. Key skills include proficiency in MLOps tools, backend development, cloud environments, and CI/CD pipelines.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
December 11, 2025
🕒 - Duration
More than 6 months
-
🏝️ - Location
Hybrid
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Sunnyvale, CA
-
🧠 - Skills detailed
#Kubernetes #Java #Cloud #Data Processing #Docker #Monitoring #Azure #ML (Machine Learning) #Data Science #AI (Artificial Intelligence) #JavaScript #Spark (Apache Spark) #MLflow #SageMaker #Python #AWS (Amazon Web Services) #GCP (Google Cloud Platform) #Deployment
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Conch Technologies, is seeking the following. Apply via Dice today!
Hi, No H1s please
Title : MLops Engineer
Duration: 12 months contract
Location: Sunnyvale, CA ( 3 days onsite 2 days remote )
Required Skills:
Overview
We are seeking a skilled Machine Learning Engineer with strong MLOps capabilities to help design, build, and scale machine learning systems from development through production. This role focuses on operationalizing models, building reliable infrastructure, and supporting data scientists in deploying and maintaining machine learning solutions.
Qualifications
Required
• Strong proficiency in end-to-end machine learning engineering, including data preparation, feature pipelines, deployment, and monitoring.
• Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or similar.
• Backend or full-stack development experience with one or more languages (Python, Java, JavaScript/Node, Go, etc.).
• Familiarity with cloud environments (AWS, Google Cloud Platform, Azure) and containerization (Docker, Kubernetes).
• Experience building automated CI/CD pipelines for ML workflows.
• Strong understanding of model versioning, reproducibility, and experiment tracking.
• Ability to work in a fast-paced environment and collaborate across data science, engineering, and product teams.
Preferred
• Experience building internal ML platforms or developer tools.
• Knowledge of distributed systems and large-scale data processing (Spark, Flink, Beam, etc.).
• Familiarity with monitoring tools for ML models (e.g., Evidently AI, Fiddler, Arize, WhyLabs).
• Experience deploying multiple models in production environments.
With Regards,
Chanakya Bhadrachalam
Sr. IT Recruiter
Desk:
EmaiL:
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Conch Technologies, is seeking the following. Apply via Dice today!
Hi, No H1s please
Title : MLops Engineer
Duration: 12 months contract
Location: Sunnyvale, CA ( 3 days onsite 2 days remote )
Required Skills:
Overview
We are seeking a skilled Machine Learning Engineer with strong MLOps capabilities to help design, build, and scale machine learning systems from development through production. This role focuses on operationalizing models, building reliable infrastructure, and supporting data scientists in deploying and maintaining machine learning solutions.
Qualifications
Required
• Strong proficiency in end-to-end machine learning engineering, including data preparation, feature pipelines, deployment, and monitoring.
• Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or similar.
• Backend or full-stack development experience with one or more languages (Python, Java, JavaScript/Node, Go, etc.).
• Familiarity with cloud environments (AWS, Google Cloud Platform, Azure) and containerization (Docker, Kubernetes).
• Experience building automated CI/CD pipelines for ML workflows.
• Strong understanding of model versioning, reproducibility, and experiment tracking.
• Ability to work in a fast-paced environment and collaborate across data science, engineering, and product teams.
Preferred
• Experience building internal ML platforms or developer tools.
• Knowledge of distributed systems and large-scale data processing (Spark, Flink, Beam, etc.).
• Familiarity with monitoring tools for ML models (e.g., Evidently AI, Fiddler, Arize, WhyLabs).
• Experience deploying multiple models in production environments.
With Regards,
Chanakya Bhadrachalam
Sr. IT Recruiter
Desk:
EmaiL:






