MLOps Engineer

• Job Description Summary:
• We are seeking a skilled Machine Learning Ops Engineer with 3–5 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

Key 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.

What You’ll Need to Be Successful (Required Skills):

3 -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 you’ll work on exciting challenges that shape the future of Healthcare. You’ll 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.

Netsmart desires to provide a healthy and safe workplace and, as a government contractor, Netsmart is committed to maintaining a drug-free workplace in accordance with applicable federal law. Pursuant to Netsmart policy, all post-offer candidates are required to successfully complete a pre-employment background check, which is provided at Netsmart’s sole expense.