Associate Machine Learning Ops Engineer

Associate Machine Learning Ops Engineer

Ensign is committed to harnessing the power of artificial intelligence and machine learning to drive cutting-edge solutions for Cyber Security. We are looking for a skilled Associate Machine Learning Ops Engineer with expertise in model deployment and AI model building to join our dynamic team. This role is crucial in ensuring that our machine learning models are effectively developed, optimized, and deployed to production environments.

Responsibilities:

• Develop and maintain CI/CD pipelines for deploying machine learning models to production environments.
• Work closely with DevOps and engineering teams to integrate models into applications and services.
• Monitor and manage deployed models to ensure optimal performance, scalability, and reliability.
• Automate the deployment process to minimize manual intervention and errors.
• Perform hyperparameter tuning, model evaluation, and validation to ensure robust and efficient models.
• Identify and resolve bottlenecks in model performance, optimizing for speed, accuracy, and resource utilization.

Model Development:

• Design, develop, and optimize machine learning models tailored to solve specific business problems.
• Collaborate with data scientists and domain experts to understand data, define features, and build models using tools such as TensorFlow, PyTorch, or Scikit-Learn.
• Implement and test various machine learning algorithms, ensuring high accuracy, performance, and scalability.

Collaboration and Communication:

• Collaborate with cross-functional teams, including data engineering and software development to ensure alignment and integration of machine learning models with business objectives.
• Communicate model outcomes, limitations, and assumptions to stakeholders in a clear and concise manner.

Research and Innovation:

• Stay updated with the latest advancements in machine learning, AI, and related technologies.
• Experiment with new algorithms, tools, and frameworks to enhance the capabilities of our machine learning models.

Requirements:

• Proven experience in developing and deploying machine learning models in production environments.
• Proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Keras, or Scikit-Learn.
• Strong understanding of MLOps/DevOps principles and experience with tools like Gitlab CI/CD, MLFlow, Docker, Kubernetes, or similar.
• Familiarity with cloud platforms such as AWS, Google Cloud, or Azure, and experience in deploying models on these platforms.
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Strong communication skills and the ability to explain complex concepts to non-technical stakeholders.

Preferred Skills:

• Knowledge of big data technologies like Hadoop, Spark, or similar.
• Understanding of data preprocessing, feature engineering, and data visualization techniques.
• Experience with version control systems like Git.