Remote AI/ML Production Deployment Engineer

SecondTalent; Town of Boston (NY); Hybrid; USD 95,000 - 135,000; Full time

Benefits offered by this job

Competitive salary

Opportunities for growth

Work on cutting-edge technology

Job summary

A leading tech company is looking for an AI/ML Model Deployment Engineer to deploy machine learning models into production. Responsibilities include designing infrastructure, managing model performance, and collaborating with data scientists. Candidates should have a Bachelor's degree in Computer Science or a related area, with expertise in container technologies, cloud platforms, and programming languages like Python. This position offers competitive salary based on experience and location, with opportunities for growth in a rapidly evolving field.

Qualifications

• Foundational knowledge of ML concepts and technologies.
• Proficiency in Python and familiarity with Go, Java, or Scala.
• Experience with AWS, Google Cloud, or Azure services.

Responsibilities

• Design and implement infrastructure necessary to deploy ML models.
• Work closely with data scientists to understand ML model requirements.
• Handle model versioning, feature serving, and performance monitoring.

Skills

Machine Learning Fundamentals

Containerization and Orchestration

Cloud Platforms

Programming Languages

CI/CD for ML

Model Serving Frameworks

Monitoring and Observability

API Development

Performance Optimization

Infrastructure as Code

Education

Bachelor's degree in Computer Science

Job description

A leading tech company is looking for an AI/ML Model Deployment Engineer to deploy machine learning models into production. Responsibilities include designing infrastructure, managing model performance, and collaborating with data scientists. Candidates should have a Bachelor's degree in Computer Science or a related area, with expertise in container technologies, cloud platforms, and programming languages like Python. This position offers competitive salary based on experience and location, with opportunities for growth in a rapidly evolving field.