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Machine Learning Ops Engineer

2 months ago

bangalore, India New Relic Full time

Job description : ML Ops Engineer


What You'll Do


As an MLOps Engineer at New Relic, you'll play a crucial role in bridging the gap between machine learning development and operations. You'll work with a talented team to build and maintain the infrastructure that supports our AI and machine learning initiatives. Your responsibilities will include:

  • Designing and implementing scalable ML environments that enhance the productivity of our ML engineers and data scientists
  • Building and deploying reproducible and scalable ML solutions on cloud infrastructure
  • Implementing versioning for machine learning datasets and models, and tracking experiments
  • Designing and building continuous integration and deployment pipelines for AI applications
  • Setting up ML monitoring and tracing tools to maintain and optimize our ML solutions
  • Collaborating with data scientists, software engineers, and product managers to integrate ML models into the observability platform


Who We're Looking For

We're seeking a passionate engineer who is deeply interested in efficiently developing, deploying, and maintaining AI applications within the context of observability and monitoring solutions. You should be driven to deliver impactful solutions and thrive in a collaborative, fast-paced environment.


Required Skills

  • Bachelor's or Master's degree in computer science, engineering or related field.
  • 2+ years of experience in software development, machine learning engineering or related field.
  • Strong understanding of machine learning concepts and frameworks, including TensorFlow, PyTorch, Scikit-learn, etc.
  • Experience with open source tools such as MLflow and Kubeflow
  • Familiarity with DevOps practices and tools such as Kubernetes, Docker, Jenkins, CI/CD, Git.
  • Experience in developing and deploying machine learning models in a production environment.
  • Proficiency in programming languages commonly used in data science and MLOps, such as Python
  • Continuously optimize and fine-tune ML models for better performance
  • Identify and address bottlenecks in the system to enhance overall efficiency
  • Familiarity with infrastructure as code (IaC) tools like Terraform
  • Strong analytical and problem-solving skills


Preferred Skills

  • Experience with data lake technologies such as Spark, S3 and Snowflake
  • Experience with time-series data and forecasting models.
  • Experience with MLOps platforms such as Kubeflow, MLFlow, Sagemaker etc.
  • Familiarity with database technologies such as SQL, NoSQL, etc.