Senior ML Engineer Job at Next Ventures in New Bremen
Next Ventures, New Bremen, OH, United States
Senior Machine Learning Engineer Your New Career As a Senior Machine Learning Engineer, you will be part of a global team developing distributed sensing solutions that help optimize critical infrastructure, protect people, and safeguard the environment. Using advanced sensing technologies combined with machine learning, the team delivers reliable real-time insights across assets such as pipelines, power cables, and railway systems.
In this role, you will contribute to solutions deployed worldwide, working in a collaborative, cross-disciplinary engineering environment that values technical rigor, long-term quality, and practical innovation.
Your Responsibilities Turn machine learning proof-of-concepts into robust, production-ready systems for real-time analysis on edge devices and backend platforms
Lead the design and implementation of scalable ML pipelines and data processing components for high-volume sensor data
Drive engineering best practices within the team
Build and maintain CI/CD workflows and automated testing for ML applications, ensuring reliability and reproducibility
Collaborate closely with data scientists, platform engineers, data engineers, and domain experts to shape system architecture and integrate ML solutions into the overall product landscape
Your Profile Degree in computer science, machine learning, or a related field, or equivalent practical experience
5+ years of professional experience in software engineering or ML engineering, including production ML or data-intensive systems
Strong programming skills in Python, with the ability to write structured, maintainable, and efficient code
Advanced programming skills in at least one statically typed language (e.g., C++, Rust, Go, or Java)
Deep understanding of the MLOps lifecycle, including data and model versioning, deployment, monitoring, and continuous improvement
Experience with containerization (e.g., Docker) and CI/CD pipelines, along with modern testing practices
Nice to have Experience operating ML systems in production, including monitoring model performance, drift detection, and incident handling
Experience with real-time or near-real-time systems, streaming data, or IoT environments, including edge deployment constraints
What’s Offered Challenging and impactful work using state-of-the-art technology
Open, collaborative, and respectful working environment
International, team-oriented culture
Competitive compensation and benefits, including flexible working hours
Opportunities for personal development, career growth, and performance-based incentives
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In this role, you will contribute to solutions deployed worldwide, working in a collaborative, cross-disciplinary engineering environment that values technical rigor, long-term quality, and practical innovation.
Your Responsibilities Turn machine learning proof-of-concepts into robust, production-ready systems for real-time analysis on edge devices and backend platforms
Lead the design and implementation of scalable ML pipelines and data processing components for high-volume sensor data
Drive engineering best practices within the team
Build and maintain CI/CD workflows and automated testing for ML applications, ensuring reliability and reproducibility
Collaborate closely with data scientists, platform engineers, data engineers, and domain experts to shape system architecture and integrate ML solutions into the overall product landscape
Your Profile Degree in computer science, machine learning, or a related field, or equivalent practical experience
5+ years of professional experience in software engineering or ML engineering, including production ML or data-intensive systems
Strong programming skills in Python, with the ability to write structured, maintainable, and efficient code
Advanced programming skills in at least one statically typed language (e.g., C++, Rust, Go, or Java)
Deep understanding of the MLOps lifecycle, including data and model versioning, deployment, monitoring, and continuous improvement
Experience with containerization (e.g., Docker) and CI/CD pipelines, along with modern testing practices
Nice to have Experience operating ML systems in production, including monitoring model performance, drift detection, and incident handling
Experience with real-time or near-real-time systems, streaming data, or IoT environments, including edge deployment constraints
What’s Offered Challenging and impactful work using state-of-the-art technology
Open, collaborative, and respectful working environment
International, team-oriented culture
Competitive compensation and benefits, including flexible working hours
Opportunities for personal development, career growth, and performance-based incentives
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