ML Ops Engineer, Coactive

• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field
• 5+ years of experience in ML Ops, DevOps, or related roles
• Strong programming skills in Python
• Proficiency with ML frameworks such as MLFlow, TensorFlow, PyTorch, or scikit-learn
• Hands-on experience using big data technologies such as Spark and Kafka
• Experience with cloud platforms such as AWS, Google Cloud, or Azure
• Solid understanding of containerization and orchestration technologies like Docker and Kubernetes
• Experience with data engineering and ETL processes
• Experience of database systems, both SQL and NoSQL
• Familiarity with CI/CD tools such as Github Actions, Jenkins, GitLab CI, or CircleCI
• Experience with monitoring tools like Datadog, NewRelic, or similar
• Strong problem-solving skills and attention to detail
• Excellent communication and collaboration abilities

Desirable

• As a founding ML Ops Engineer at CoactiveAI, you will play a crucial role in designing, building, and maintaining our ML infrastructure
• You will work closely with research scientists, ML Engineers, software engineers, and product managers to deploy and monitor machine learning models in production
• Your expertise will ensure the robustness, scalability, and reliability of our AI solutions
• Design and implement scalable and reliable ML pipelines
• Automate the deployment and monitoring of ML models
• Collaborate with ML Engineers, Applied ML Researchers and software engineers to integrate ML models into applications
• Optimize model performance and scalability
• Enable Research scientists with experimentation, validation and productionisation of new models
• Monitor and troubleshoot production ML systems to ensure high availability and reliability
• Implement and enforce best practices for ML Ops, including versioning, testing, and validation