Senior Machine Learning Engineer

• Drive and improve MLOps practices across the ML environment

• Build and optimize CI/CD pipelines using GitLab

• Implement ML experiment tracking and model management with MLflow

• Productionize and deploy machine learning models using AWS SageMaker

• Design and maintain scalable ML and data pipelines

• Develop and maintain Python-based ML and data infrastructure

• Implement monitoring and observability for ML systems

• Provide technical guidance and mentor Data Scientists, Data Engineers, and MLOps Engineers

• Apply software engineering best practices, including testing, documentation, and system design

• Collaborate with Product Managers, Data Scientists, Engineers, and business stakeholders

• Evaluate and introduce new technologies to improve ML capabilities

Requirements

• 5+ years of professional experience in Machine Learning Engineering

• Strong experience deploying and maintaining production ML systems

• Expert-level Python skills and knowledge of the data science ecosystem

• Hands-on experience with AWS, preferably AWS SageMaker

• Strong knowledge of MLOps practices and lifecycle

• Practical experience with MLflow

• Experience with GitLab CI/CD

• Experience with at least one major deep learning framework, e.g. PyTorch or TensorFlow

• Experience designing and building scalable ML and data pipelines

• Experience with ML system monitoring and observability

• Ability to design, document, and communicate complex technical architectures

• Experience mentoring and providing technical guidance to other engineers and data scientists

• Strong communication and stakeholder management skills

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience

• Preferred: Master's or PhD in Computer Science, AI, or Machine Learning

• Preferred: Experience with Prometheus, Grafana, or Evidently AI

• Preferred: Experience working with large-scale recommender systems

• Preferred: Strong understanding of software engineering and system design principles

Core Competencies

Demonstrates expertise in Machine Learning Engineering with a strong focus on MLOps practices, CI/CD pipeline optimization, and productionizing ML models using AWS SageMaker. Proficient in Python and experienced in mentoring teams while implementing best software engineering practices.

Highest-signal resume keywords

• Machine Learning Engineering

• AWS SageMaker

• Python Programming

• MLOps Practices

• CI/CD Pipeline Development

ATS Optimization Keywords

Hard Skills

• Machine Learning Engineering

• Python Programming

• MLOps Practices

• CI/CD Pipeline Development

• MLflow

• Deep Learning Frameworks

• Monitoring and Observability

• Data Pipeline Design

• Technical Documentation

• System Design

Soft Skills

• Technical Guidance

• Mentoring

• Communication

• Stakeholder Management

Certifications & Qualifications

• Bachelor's Degree in Computer Science

• Master's or PhD in Computer Science, AI, or Machine Learning

Industry Keywords

• MLOps

• Machine Learning

• Data Science Ecosystem

• Recommender Systems

Tools & Technologies

• AWS

• GitLab

• MLflow

• Prometheus

• Grafana

• Evidently AI