Senior Machine Learning Engineer

Jobtailor; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

Jobtailor seeks an experienced ML Engineer to design and implement scalable ML architectures and applications. You will develop and review model code, build optimized data pipelines, and ensure production models run reliably at scale.

Applicants should have 4+ years in Python/Scala/Java, with 2+ years deploying ML solutions in AWS, Azure, or GCP. Collaboration with Product and Data Science teams is essential in this role.

Qualifications

• Bachelor's degree required; advanced degree preferred.
• 4+ years programming with Python/Scala/Java.
• 3+ years designing data-intensive distributed solutions.
• 2+ years productionizing, monitoring, and maintaining models.
• No immigration sponsorship for employment authorization.

Responsibilities

• Design ML architectures and implement applications.
• Develop and review model and application code.
• Ensure high availability and performance of ML apps.
• Build data pipelines feeding ML models.
• Retrain, monitor, and maintain production models.
• Collaborate with Product and Data Science teams on solutions.
• Apply CI/CD, test automation, and monitoring for ML software.

Skills

ML Architecture Design

Python Programming

Distributed Computing

Data Pipeline Development

Cloud ML Solutions

Education

Bachelor's Degree

Master's or PhD preferred

Tools

Scikit-learn

PyTorch

Dask

Spark

TensorFlow

AWS

Azure

Google Cloud Platform

Job description

• Participate in detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms
• Design machine learning architectures
• Develop and review model and application code
• Ensure high availability and performance of machine learning applications
• Design, build, and deliver ML models and components solving real-world business problems in collaboration with Product and Data Science teams
• Make ML infrastructure decisions involving model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
• Write and test application code, develop and validate ML models, and automate testing and deployment
• Collaborate on a cross-functional Agile team creating and enhancing big data and ML software
• Retrain, maintain, and monitor production models
• Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines feeding ML models
• Apply continuous integration and continuous deployment practices, including test automation and monitoring
• Manage code to reduce vulnerabilities, govern models from a risk perspective, and apply Responsible and Explainable AI best practices
• Use Python, Scala, or Java

Requirements

• Bachelor's Degree
• At least 4 years of experience programming with Python, Scala, or Java (internship experience does not apply)
• At least 3 years of experience designing and building data-intensive solutions using distributed computing
• At least 2 years of on-the-job experience with an industry-recognized ML framework, such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• At least 1 year of experience productionizing, monitoring, and maintaining models
• No employer sponsorship or immigration-related support for employment authorization
• Preferred: 1+ years building, scaling, and optimizing ML systems
• Preferred: 1+ years with data gathering and preparation for ML models
• Preferred: 2+ years developing performant, resilient, and maintainable code
• Preferred: Experience deploying ML solutions in AWS, Azure, or Google Cloud Platform
• Preferred: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• Preferred: 3+ years with distributed file systems or multi-node database paradigms
• Preferred: Contributions to open-source ML software
• Preferred: Authorship or co-authorship of a paper on an ML technique, model, or proof of concept
• Preferred: 3+ years building production-ready data pipelines that feed ML models
• Preferred: Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• Preferred: Experience leveraging interactive AI tooling beyond basic code completion

Core Competencies

Demonstrates expertise in designing and implementing machine learning architectures and models, with a strong focus on optimizing performance and scalability. Proficient in programming with Python, Scala, or Java, and experienced in building data-intensive solutions using distributed computing and industry-recognized ML frameworks.

Highest-signal resume keywords

• Machine Learning Architecture Design
• Python Programming
• Data Pipeline Development
• Model Productionization and Monitoring
• Cloud-Based ML Solutions

Hard Skills

• Machine Learning
• Data Engineering
• Model Validation
• Hyperparameter Tuning
• Continuous Integration
• Continuous Deployment
• Distributed Computing
• Test Automation
• Performance Optimization
• Data Feature Selection

Industry Keywords

• Responsible AI
• Explainable AI
• Big Data
• Cross-Functional Collaboration
• Agile Methodology

Tools & Technologies

• Scikit-learn
• PyTorch
• Dask
• Spark
• TensorFlow
• AWS
• Azure
• Google Cloud Platform