Software Engineer MLOps

We are seeking a skilled Machine Learning Ops Engineer with 4-5 years of experience to design, deploy, and maintain scalable machine learning systems in production. The ideal candidate will have hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn, along with strong expertise in cloud platforms (AWS, Azure, or GCP) and containerization technologies like Docker and Kubernetes.

Job Description

Role & responsibilities :

• Design, implement and maintain ML pipelines for model training, validation, and deployment
• Automate model training, testing and deployment (CI/CD of ML models)
• Monitor model performance, data drift, and system health in production environments.
• Deploy models in pre-prod, prod environments.
• Collaborate with data scientists to operationalize machine learning models and algorithms
• Implement version control for models, datasets, and ML experiments using MLOps tools
• Optimize ML infrastructure for scalability, reliability, and cost-effectiveness
• Troubleshoot and resolve issues related to model deployment and production systems
• Maintain documentation for ML workflows, deployment processes, and system architecture
• This position may require availability outside of standard business hours as part of a rotational on-call schedule.

Preferred candidate profile

• 4 -5 years of experience in software development, DevOps, or data engineering
• Proficiency in Python, SQL, and at least one ML framework such as TensorFlow, PyTorch, Scikit-learn
• Experience with containerization (Docker) and orchestration tools (Kubernetes)
• Knowledge of cloud platforms such as AWS, Azure, GCP and their ML services
• Understanding of CI/CD pipelines, version control (Git), and infrastructure as code
• Familiarity with monitoring tools and logging frameworks for production systems
• Experience with data pipeline tools such as Apache Airflow, Kubeflow, or similar
• Strong problem-solving skills and ability to work in fast-paced, collaborative environments

Preferred Skills:

• Experience with MLOps platforms such as MLflow, Weights & Biases, Neptune
• Knowledge of streaming data processing such as Kafka, Kinesis
• Familiarity with infrastructure monitoring tools such as Prometheus, Grafana
• Understanding of model interpretability and explainability techniques
• Experience with feature stores and data versioning tools
• Certification in cloud platforms such as AWS ML, Azure AI, GCP ML

Education/ Certifications:

Bachelor’s degree in computer science engineering, Information Technology engineering or any engineering related field.

Why Join Us?

• At Netsmart youll work on exciting challenges that shape the future of Healthcare. Youll have the opportunity to:
• Collaborate with talented professionals passionate about technology.
• Work in a supportive and inclusive environment where your growth is prioritized.
• Access professional development opportunities, including certifications and training.
• Enjoy a competitive compensation package and comprehensive benefits.

Netsmart is proud to be an equal opportunity workplace and is an affirmative action employer, providing equal employment and advancement opportunities to all individuals. We celebrate diversity and are committed to creating an inclusive environment for all associates. All employment decisions at Netsmart, including but not limited to recruiting, hiring, promotion and transfer, are based on performance, qualifications, abilities, education and experience. Netsmart does not discriminate in employment opportunities or practices based on race, color, religion, sex (including pregnancy), sexual orientation, gender identity or expression, national origin, age, physical or mental disability, past or present military service, or any other status protected by the laws or regulations in the locations where we operate.