Senior ML OPS Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior ML Ops Engineer in Plano, TX, with a long-term contract and immediate start. Requires 8+ years of experience, expertise in AWS, CI/CD, Docker, Kubernetes, and Python, along with strong MLOPS pipeline management skills.
🌎 - Country
United States
💱 - Currency
$ USD
💰 - Day rate
Unknown
Unknown
🗓️ - Date discovered
May 20, 2025
🕒 - Project duration
Unknown
🏝️ - Location type
On-site
📄 - Contract type
Unknown
🔒 - Security clearance
Unknown
📍 - Location detailed
Plano, TX
🧠 - Skills detailed
#Databricks #Terraform #ML (Machine Learning) #AI (Artificial Intelligence) #Docker #Langchain #S3 (Amazon Simple Storage Service) #Deployment #Lambda (AWS Lambda) #Programming #Security #Datadog #Cloud #Data Privacy #DevOps #Data Science #GitHub #AWS (Amazon Web Services) #Bash #Automation #Python #ML Ops (Machine Learning Operations) #Scripting #EC2 #IAM (Identity and Access Management) #Network Security #VPC (Virtual Private Cloud) #SageMaker #Scrum #Model Deployment #Kubernetes #DynamoDB #Monitoring #Continuous Deployment #Scala #AWS S3 (Amazon Simple Storage Service)
Role description
Hope you are doing well.
I am Srinivas from Futran Solutions. My client is looking for the below requirement. If you are interested. Please reach me out msrinivas@futransolutions.com /(609)-945-2335
Job Title: Sr. ML Ops Engineer
Location: Onsite Plano, TX - Client office in Plano, TX (In Person Interview, So Local Candidates Only)
Duration: Long-term
Start date: Immediate.
Job Description:
DXC Team is seeking an AWS MLOPS engineer to help configure, deploy and operationalize platforms for data science.
Responsibilities:
Develop and implement automated pipelines for deploying, monitoring, and updating machine learning models in production environments.
Design and maintain continuous integration/continuous deployment (CI/CD) pipelines specifically for ML models, ensuring smooth transitions from development to production.
Monitor model performance in real-time, detecting any degradation or anomalies, and implement automated processes for model retraining and versioning.
Manage and optimize the infrastructure required for ML workflows, including cloud environments (AWS), containerization (Docker), and orchestration (Kubernetes).
Work closely with data scientists to understand model requirements, and with engineering teams to ensure the integration of models into production systems.
Ensure model and data versioning are managed effectively, ensuring the reproducibility of experiments and models.
Ensure that the ML models are deployed securely and comply with relevant regulatory requirements (e.g., data privacy laws, security standards).
Document processes, workflows, and best practices for model deployment, monitoring, and maintenance, ensuring knowledge sharing across teams.
Primary Skills:
Cloud Platforms: AWS: S3, DynamoDB, EC2, VPC, Lambda, CloudWatch etc.
CI/CD Tools: GitHub Actions
Container Technologies: Docker, Kubernetes
Sagemaker
Scripting Languages: Python, Bash
Automation: Terraform and Python
Datadog, CloudWatch
Devops pipeline creation, deployment
Nice to have :
Type Script
Databricks, Glue
Qualifications:
Bachelors degree with 8+ years of overall experience in building cloud infrastructureservices, minimum of 5+ years of experience in designing, building, and maintaining MLOPS pipeline.
Results-oriented MLOPS professional with a strong background in machine learning, operations, and DevOps. Proven track record of deploying and managing machine learning models at scale. Adept at collaborating with cross-functional teams to deliver efficient and scalable solutions. Proficient in programming languages such as Python, and well-versed in a range of DevOps tools, cloud services, database technologies, generative AI, Langchain, LLM, LLMOPS, and MLOPS.
Knowledge in all aspects of DevOps (source control, continuous integration, deployments, etc.)
Knowledge in security implementation best practices on IAM policies, KMS encryption, Secrets Management, Network Security Groups etc.
Experience working in the SCRUM Environment.
Thanks & Regards,
Name: Srinivasa Reddy Mallu.
Designation: Team Lead
Contact +1 (609)-945-2335, Ext: 9068
Email Id: msrinivas@futransolutions.com
Hope you are doing well.
I am Srinivas from Futran Solutions. My client is looking for the below requirement. If you are interested. Please reach me out msrinivas@futransolutions.com /(609)-945-2335
Job Title: Sr. ML Ops Engineer
Location: Onsite Plano, TX - Client office in Plano, TX (In Person Interview, So Local Candidates Only)
Duration: Long-term
Start date: Immediate.
Job Description:
DXC Team is seeking an AWS MLOPS engineer to help configure, deploy and operationalize platforms for data science.
Responsibilities:
Develop and implement automated pipelines for deploying, monitoring, and updating machine learning models in production environments.
Design and maintain continuous integration/continuous deployment (CI/CD) pipelines specifically for ML models, ensuring smooth transitions from development to production.
Monitor model performance in real-time, detecting any degradation or anomalies, and implement automated processes for model retraining and versioning.
Manage and optimize the infrastructure required for ML workflows, including cloud environments (AWS), containerization (Docker), and orchestration (Kubernetes).
Work closely with data scientists to understand model requirements, and with engineering teams to ensure the integration of models into production systems.
Ensure model and data versioning are managed effectively, ensuring the reproducibility of experiments and models.
Ensure that the ML models are deployed securely and comply with relevant regulatory requirements (e.g., data privacy laws, security standards).
Document processes, workflows, and best practices for model deployment, monitoring, and maintenance, ensuring knowledge sharing across teams.
Primary Skills:
Cloud Platforms: AWS: S3, DynamoDB, EC2, VPC, Lambda, CloudWatch etc.
CI/CD Tools: GitHub Actions
Container Technologies: Docker, Kubernetes
Sagemaker
Scripting Languages: Python, Bash
Automation: Terraform and Python
Datadog, CloudWatch
Devops pipeline creation, deployment
Nice to have :
Type Script
Databricks, Glue
Qualifications:
Bachelors degree with 8+ years of overall experience in building cloud infrastructureservices, minimum of 5+ years of experience in designing, building, and maintaining MLOPS pipeline.
Results-oriented MLOPS professional with a strong background in machine learning, operations, and DevOps. Proven track record of deploying and managing machine learning models at scale. Adept at collaborating with cross-functional teams to deliver efficient and scalable solutions. Proficient in programming languages such as Python, and well-versed in a range of DevOps tools, cloud services, database technologies, generative AI, Langchain, LLM, LLMOPS, and MLOPS.
Knowledge in all aspects of DevOps (source control, continuous integration, deployments, etc.)
Knowledge in security implementation best practices on IAM policies, KMS encryption, Secrets Management, Network Security Groups etc.
Experience working in the SCRUM Environment.
Thanks & Regards,
Name: Srinivasa Reddy Mallu.
Designation: Team Lead
Contact +1 (609)-945-2335, Ext: 9068
Email Id: msrinivas@futransolutions.com
