Remote - AI Engineer

We are seeking a highly skilled AI Engineer with a robust background in full stack development to join our dynamic team. The ideal candidate will have a proven track record in developing and deploying MLOps platforms that enable real-time AI and advanced analytics, ideally on-premises. This role involves designing, implementing, and maintaining the MLOps platform, ensuring seamless integration with our existing infrastructure. The ideal candidate will also have some experience with SCADA systems and will have some experience with BESS. If you are passionate about leveraging your expertise in full stack development to drive AI innovations, we invite you to apply.

Responsibilities:

• Design and Implementation: Design, implement, and maintain an MLOps platform for real-time AI and advanced analytics applications.
• Collaboration: Collaborate with data scientists, developers, and IT teams to streamline the deployment and monitoring of machine learning models.
• Pipeline Development: Develop automated pipelines for model training, validation, deployment, and monitoring.
• Scalability and Reliability: Ensure the platform supports scalability, reliability, and security needs.
• Integration: Integrate the MLOps platform with existing data sources, data lakes, and data warehouses.
• Performance Monitoring: Monitor the performance of AI models and the platform, and implement improvements as necessary.
• Support: Provide support for both development and production environments.
• Documentation: Document platform architecture, processes, and workflows.
• Continuous Learning: Stay updated with the latest advancements in MLOps, AI, and relevant technologies.

Requirements:

• Experience: Proven experience as an AI Engineer with a strong background in full stack development.
• MLOps Expertise: Hands-on experience in building and maintaining MLOps platforms, particularly for real-time applications.
• Programming Skills: Strong programming skills in Python and JavaScript/TypeScript.
• Frameworks & Libraries: Proficiency with frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn.
• Containerization & Orchestration: Experience with containerization and orchestration technologies like Docker and Kubernetes.
• CI/CD Knowledge: Familiarity with CI/CD tools such as Jenkins, GitLab CI, or CircleCI.
• Data Engineering: Experience in data engineering, including working with data pipelines and ETL processes.
• Database Technologies: Knowledge of database technologies such as SQL and NoSQL (e.g., MongoDB, Cassandra).
• On-Premises: Hands-on experience with on-premises deployments.
• Real-Time Processing: Familiarity with real-time data processing frameworks (e.g., Apache Kafka, Apache Flink).
• DevOps Practices: Strong understanding of DevOps practices and tools.
• Problem-Solving: Excellent problem-solving skills and a proactive attitude.
• Communication: Strong communication skills and the ability to work collaboratively in a team environment.
• Bachelor's degree in Computer Science or related field or equivalent combination of industry-related professional experience and education.

Preferred Qualifications:

• MLOps Tools: Experience with MLOps tools such as MLflow, Kubeflow, or TFX.
• Monitoring & Logging: Knowledge of monitoring and logging tools like Prometheus, Grafana, or ELK stack.
• Data Visualization: Familiarity with data visualization tools (e.g., Power BI, Tableau).
• Web Development: Previous experience in developing web applications using frameworks such as React, Angular, or Vue.js.
• Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• SCADA Systems: Experience with Supervisory Control and Data Acquisition (SCADA) systems.
• Alteryx: Experience with Alteryx for data blending and advanced analytics.

Tech Stack:

• Programming Languages: Python, JavaScript/TypeScript
• AI/ML Frameworks: TensorFlow, PyTorch, scikit-learn
• Containerization & Orchestration: Docker, Kubernetes
• CI/CD Tools: Jenkins, GitLab CI, CircleCI
• Data Processing: Apache Kafka, Apache Flink
• Databases: SQL, NoSQL (MongoDB, Cassandra)
• Cloud Platforms: AWS, Azure, GCP
• MLOps Tools: MLflow, Kubeflow, TFX
• Monitoring & Logging: Prometheus, Grafana, ELK stack
• Web Frameworks: React, Angular, Vue.js (Preferred)
• Data Visualization: Alteryx (Preferred)
• SCADA Systems: SCADA Systems (Preferred)