Machine Learning /MLOps Engineer

Vdart - San Antonio, TX

Full-time - Mid Level

San Antonio, TX

1,001-5,000 employees

Professional, Scientific, and Technical Services

About the position

The Machine Learning / MLOps Engineer role focuses on building and deploying machine learning models and data ingestion pipelines at a large scale. This position requires collaboration with stakeholders to support data infrastructure needs and optimize processes for efficiency. The engineer will also conduct machine learning experiments and implement suitable ML tools to enhance data delivery processes.

Responsibilities

• Build batch and streaming data pipelines at petabyte scale.
• Develop and deploy machine learning / AI models in the cloud.
• Run ML tests, perform statistical analysis, and fine-tune using test results.
• Experiment with and implement suitable ML algorithms and tools.
• Collaborate with stakeholders to address data-related technical issues and support data infrastructure needs.
• Enhance data delivery processes and redesign infrastructure for scalability.
• Identify, design, and implement internal process improvements for efficiency.

Requirements

• Minimum of 8 years in data engineering, including 3 years of MLOps experience.
• Strong coding skills, especially in Python and SQL.
• Experience with data and ML pipeline implementation using Python, R, SQL, Docker, Kubernetes, and Domino Data Lab.
• Expertise in cloud platforms and data tools, specifically Snowflake, AWS, and Kafka.
• Experience with Control-M and Airflow for managing data workflows.
• Familiar with Agile development methodologies.
• Deep understanding of math, probability, statistics, and algorithms.
• Strong problem-solving and troubleshooting skills.
• Excellent interpersonal and teamwork abilities.

Nice-to-haves

• Experience with Gen-AI and AWS SageMaker is a plus.
• Snowflake and AWS certifications are preferred.
• Experience in the financial domain is a plus.

Benefits

• Long-term contract position with potential for growth.
• Opportunity to work with a diverse team across multiple countries.
• Engagement in projects with Fortune 500 companies.