MLOps Engineer

Who We Are:

At CNTXT, we leverage cutting-edge technology to provide your enterprise with data that customizes powerful base generative models, unlocking AI's safe and transformative value. Our CNTXT Data Engine has all the tools and features you need to collect, curate, and annotate high-quality data. We offer robust capabilities to evaluate and optimize your models, ensuring that they perform at their best. Through our advanced RLHF (Reinforcement Learning from Human Feedback), data generation, model evaluation, safety, and alignment solutions, we power the most sophisticated LLMs (Large Language Models) and generative models in the world.

About the Role: As an MLOps Engineer at CNTXT, you will play a crucial role in building and maintaining robust platforms for deploying and orchestrating machine learning models. You will leverage open-source technologies to streamline the machine learning lifecycle, from development to production.

Key Responsibilities:

Platform Development:

• Design and build scalable MLOps platforms using open-source tools and frameworks (e.g., Kubernetes, Kubeflow, MLflow).
• Develop automated pipelines for model training, deployment, and monitoring.
• Ensure platform reliability, performance, and security.

Model Deployment:

• Deploy machine learning models to production environments on-premises and in the cloud.
• Manage model versions and configurations.
• Implement strategies for model retraining and updates.

Infrastructure Management:

• Manage and optimize underlying infrastructure (e.g., compute resources, storage).
• Implement containerization and orchestration technologies.

Monitoring and Observability:

• Set up monitoring tools to track model performance, resource utilization, and errors.
• Implement observability practices to gain insights into model behavior.

Collaboration:

• Work closely with data scientists, machine learning engineers, and other stakeholders.
• Provide technical guidance and support.

Required Skills and Experience:

Technical Skills:

• Strong proficiency in Python and other programming languages.
• Experience with cloud platforms (AWS, Azure, GCP) and cloud-native technologies.
• Knowledge of containerization technologies (Docker, Kubernetes).
• Familiarity with machine learning frameworks (TensorFlow, PyTorch).
• Understanding of DevOps principles and practices.

Soft Skills:

• Problem-solving and analytical abilities.
• Strong communication and collaboration skills.
• Ability to work independently and as part of a team.

Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Proven experience in MLOps or a related field. Certifications in cloud platforms or DevOps (e.g., AWS Certified DevOps Engineer).

Benefits of Working at CNTXT: Competitive salary and benefits package. Opportunities for professional growth and development. Collaborative and supportive work environment. Exposure to cutting-edge technologies and projects. If you are a passionate and talented MLOps Engineer looking to make a significant impact in the field of machine learning, we encourage you to apply.