ML Ops Engineer

Overview

At Nortal, we create meaningful impact by building seamless digital solutions that shape a better society. We are now looking for a Senior MLOps Software Engineer to lead the design, development, and optimization of our machine learning infrastructure.

In this role, you will be instrumental in scaling our ML capabilities, ensuring smooth deployment of models, and driving operational excellence across the AI lifecycle. You’ll work closely with data scientists, engineers, and product teams to build robust, automated, and secure ML systems powering real-world applications.

Responsibilities

• Architect and implement end-to-end MLOps pipelines for training, validating, deploying, and monitoring ML models.
• Lead initiatives to build scalable, reproducible, and automated ML workflows.
• Collaborate cross-functionally with data scientists, ML engineers, and DevOps teams to integrate models into production environments.
• Establish and maintain best practices for model versioning, governance, and lifecycle management.
• Monitor and optimize model performance, infrastructure cost, and system reliability.
• Evaluate and integrate new tools and technologies to enhance the ML platform.
• Mentor junior and mid-level engineers, fostering the growth of the MLOps function.
• Ensure compliance with data privacy, security, and regulatory standards throughout the ML lifecycle.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

• 5+ years of experience in software engineering, DevOps, or MLOps, with a strong focus on ML systems.

• Proficiency in Python and hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

• Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools (Terraform, CloudFormation).

• Solid understanding of containerization and orchestration (Docker, Kubernetes).

• Experience with CI/CD practices for ML (GitHub Actions, Jenkins, Argo).

• Familiarity with ML lifecycle tools (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI).

• Excellent communication and leadership skills.

Desired qualifications

• Experience with model monitoring, drift detection, and observability tools.

• Background in data engineering or real-time data processing.

• Exposure to compliance frameworks (e.g., GDPR, HIPAA) in ML contexts.

• Contributions to open-source MLOps tools or technical communities.

• Experience leading cross-functional projects and initiatives.

We like to say that Nortal is a right-sized company – big enough to undertake and impact influential projects yet small enough to care. At Nortal, your voice is heard, and everyone’s input matters. You solve critical problems for interesting customers from different domains. You work with experienced colleagues in a warm environment. You can execute your ideas in a reasonable time frame. And what you do and learn here is universally relevant and valuable. Last, but not least, Nortal is an agile company with a low hierarchy – meaning heavy on common sense, light on rules, and substance is more important than titles! One more thing… This position can be both office-based and remote. 

#LI-Hybrid