we have a job opportunity for you MLOps Engineer based at San Diego, CA (Remote)

Hi,

Greetings from Magic Force…!!

My name is ARUN we have a job opportunity for you MLOps Engineer based at San Diego, CA (Remote). Please find the job description below, if you are available and interested, please send us your word copy of your resume with following details to arun@magicforce.us 

Job Title: MLOps Engineer.

Location: San Diego, CA (Remote).

Duration: 12+Months.

Start Date: ASAP.

Job description:

• 4+ years of experience in MLOps, DevOps, or related fields.
• Strong programming skills in Python, with experience in other languages such as Java, C++, or Scala being a plus.
• Experience with ML frameworks such as TensorFlow, PyTorch, and/or scikit-learn.
• Proficiency with CI/CD tools such as Jenkins, or GitLab CI.
• Extensive experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Hands-on experience with containerization and orchestration tools like Docker and Kubernetes.
• Knowledge of infrastructure-as-code tools such as Terraform or CloudFormation.
• Strong understanding of machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.
• Excellent problem-solving skills and the ability to work independently as well as part of a team.
• Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders

Preferred Qualifications: –

• Experience with feature stores, model registries, and monitoring tools such as MLflow, Tecton, or Seldon.
• Familiarity with data engineering tools like Apache Spark, Kafka, or Airflow.
• Knowledge of security best practices for machine learning systems.

• Experience with A/B testing and model performance monitoring.
•  

Responsibilities: –

• • Design, build, and maintain the infrastructure required for efficient development, deployment, and monitoring of machine learning models.
  • Implement CI/CD pipelines for machine learning applications.
  • Develop and manage cloud-based and on-premises solutions for model training, deployment, and monitoring.
  • Ensure the scalability, reliability, and performance of machine learning systems.
  • Collaborate with data scientists to understand and implement requirements for model serving, versioning, and reproducibility.
  • Monitor and optimize model performance in production, identifying and resolving issues proactively.
  • Automate repetitive tasks to improve efficiency and reduce the risk of human error.
  • Maintain documentation and provide training to team members on MLOps best practices.
  • Stay updated with the latest developments in MLOps tools, technologies, and methodologies.
  • Communicate and share knowledge with other team members and actively participate in various learning-sharing opportunities.

If you are interested in this position, kindly fill the details and revert back me ASAP.

From:
ARUN,
Magicforce
arun@magicforce.us
Reply to:   arun@magicforce.us