Jobs for People with MS: National MS Society

Job Summary

As a Machine Learning Operations Engineer, you will play a pivotal role in rapidly developing AI-powered software applications, with a focus on internal business applications driven by large language models. Working closely with our team of data scientists and engineers, you will leverage the latest tools and technologies to drive innovation and streamline processes. Additionally, depending on career interests, this role may involve taking on some scrum master and team coordination responsibilities.

Key Responsibilities:

• Develop and manage machine learning models in production environments on cloud platforms such as Azure, AWS, or GCP.

• Implement and optimize MLOps best practices to enhance efficiency and drive innovation.

• Design and implement machine learning governance frameworks, ensuring model versioning, explainability, and fairness.

• Build and maintain machine learning infrastructure and workflows to support scalable and efficient operations.

• Utilize a wide range of technologies, including Azure services, Python, microservices, Docker, CI/CD, Elastic Search, SQL, and NoSQL databases.

• Deploy and manage machine learning models using tools like Kubernetes, Docker, and orchestration platforms such as Kubernetes and Apache Airflow.

• Collaborate with cross-functional teams to solve complex technical challenges and drive continuous improvement.

• Ensure compliance with industry standards and best practices, with a focus on security and data integrity.

Requirements:

• Strong proficiency in MLOps methodologies and industry trends.

• Experience with ML frameworks (e.g., TensorFlow, PyTorch) and data processing libraries (e.g., pandas, NumPy).

• Solid understanding of containerization, virtualization, and infrastructure as code (IaC) principles.

• Proficiency in Python programming and version control systems (e.g., Git).

• Experience with monitoring and logging tools (e.g., Prometheus, ELK stack).

• Familiarity with CI/CD pipelines and automated testing for ML models.

• Excellent problem-solving skills and ability to work effectively in a collaborative team environment.

• Strong communication skills with proficiency in spoken and written English.

Nice to Have:

• Knowledge of security best practices in ML deployments.

• Experience with ML model deployment orchestration platforms like MLflow or Kubeflow.

Education & Experience Recommended

• Four-year or Graduate Degree in Computer Science, Information Systems, or any other related discipline or commensurate work experience or demonstrated competence.

• Typically has 7-10 years of work experience, preferably in software development, information technology, engineering environment, or a related field.

Cross-Org Skills

• Effective Communication

• Results Orientation

• Learning Agility

• Digital Fluency

• Customer Centricity

Impact & Scope

• Impacts function and leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives.

Complexity

• Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors.

Disclaimer

• This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.

Equal Opportunity Employer (EEO):

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).