MLOps Engineer
Our Client is seeking a dynamic MLOps Engineer, a forward-thinking organization leveraging cutting-edge machine learning solutions. This role is at the intersection of machine learning, software engineering, and DevOps, focusing on deploying, managing, and optimizing machine learning models in production environments. If you are passionate about operationalizing AI and ML at scale and thrive in a collaborative environment, this opportunity is for you.
Key Responsibilities
• Model Deployment & Management: Design, deploy, and maintain scalable machine learning pipelines to ensure seamless integration of ML models into production systems.
• Automation & CI/CD: Implement CI/CD pipelines to automate model training, testing, and deployment processes.
• Monitoring & Optimization: Develop monitoring systems to track model performance metrics (e.g., accuracy, latency) and proactively address issues like model drift or resource inefficiencies.
• Collaboration: Work closely with data scientists, software engineers, and DevOps teams to align ML workflows with business objectives.
• Infrastructure Management: Build and manage cloud-based infrastructure (AWS/GCP/Azure) for ML operations using tools like Docker, Kubernetes, and Terraform.
• Compliance & Security: Ensure data privacy and compliance with organizational policies while implementing secure data transfer protocols.
• Innovation & Improvement: Stay updated on the latest MLOps tools and frameworks (e.g., MLflow, Kubeflow) to continuously enhance operational efficiency.
What Success Looks Like
• Efficient deployment of robust ML models with minimal downtime.
• Automated workflows that reduce manual intervention in model retraining and updates.
• Scalable infrastructure capable of handling large datasets and complex computations.
• Clear documentation of processes, enabling cross-functional team collaboration.
Required Skills & Qualifications
• Strong programming skills in Python or Java with experience in ML frameworks like TensorFlow or PyTorch.
• Proficiency in cloud platforms (AWS/GCP/Azure) and containerization tools (Docker/Kubernetes).
• Hands-on experience with CI/CD tools (Jenkins/GitLab CI) and Infrastructure-as-Code tools (Terraform/CloudFormation).
• Familiarity with data processing frameworks (Apache Spark/Kafka) and database systems (SQL/NoSQL).
• Solid understanding of DevOps practices and Linux-based environments.
Soft Skills
• Strong communication skills to collaborate with diverse teams effectively.
• Problem-solving mindset with a proactive approach to troubleshooting complex issues.
Why Join?
Our client offers an innovative work environment where your contributions will directly impact the success of their AI-driven initiatives. You’ll have the opportunity to work on exciting projects, grow professionally, and be part of a team shaping the future of machine learning operations.
Apply