Senior MLOps Engineer - US

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior MLOps Engineer in the United States.

As a Senior MLOps Engineer, you will lead the design, development, and scaling of robust machine learning infrastructure that powers high-impact AI systems. You will bridge the gap between research and production, ensuring models are deployed efficiently, reliably, and at scale. This role offers the opportunity to work with cutting-edge AI technologies, optimize ML workflows, and implement best practices for CI/CD, monitoring, and model reproducibility. You will collaborate closely with AI researchers, engineers, and cross-functional teams to productionize prototypes and improve operational efficiency. This role is ideal for a proactive problem-solver who thrives in a fast-paced environment and wants to make a significant impact on AI-driven products.

Accountabilities

• Design, build, and maintain end-to-end ML pipelines for model training, evaluation, and deployment.
• Develop and optimize infrastructure for distributed training and model serving across GPU and cloud environments.
• Implement CI/CD workflows for ML systems, including automated testing, deployment, and retraining.
• Monitor and manage model performance, drift, and data quality in production.
• Collaborate with AI researchers and engineers to productionize POCs, ensuring reproducibility and scalability.
• Drive cost optimization and performance tuning for large-scale model training and inference.
• Contribute to internal documentation and establish best practices for MLOps processes.

Requirements

• 6–10+ years of experience in software or ML engineering, with at least 3+ years focused on MLOps or ML infrastructure.
• Strong programming skills in Python, C/C++, and Bash.
• Proven experience deploying and managing ML models in production environments.
• Expertise with Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure) for scalable ML systems.
• Hands-on experience with CI/CD pipelines (GitHub Actions, Jenkins, or similar).
• Familiarity with ML experiment tracking tools (MLflow, Weights & Biases, Kubeflow).
• Understanding of model versioning, reproducibility, and monitoring strategies.
• Excellent problem-solving, communication, and collaboration skills.
• Bonus: Experience training models from scratch, model optimization (quantization, distillation), infrastructure-as-code (Terraform, CloudFormation), distributed systems, or contributions to open-source projects.

Benefits

• 💰 Competitive Salary: $190,000–$240,000 depending on skills and experience.
• 🌴 Generous PTO & Flexible Time Off to maintain work-life balance.
• 🏥 Comprehensive Healthcare Benefits for you and your family.
• 💻 Remote Work: Flexible work environment with occasional travel for team meetings.
• 📚 Professional Growth: Opportunities to work on cutting-edge ML systems and expand technical expertise.
• 🤝 Inclusive Culture: A diverse and collaborative team that values ownership, growth, and continuous learning.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the three candidates who best match the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or assessments) are managed by their internal hiring team.

Thank you for your interest!