Lead Machine Learning Engineer, Python, AWS, SQL, GenAI

Jobtailor; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Jobtailor in New York, NY is seeking a Senior ML Engineer to productionize ML applications, design scalable architectures, and build data pipelines feeding ML models. You will collaborate with Product and Data Science teams to deliver high-performance AI at scale.

The role emphasizes cloud platforms (AWS/Azure/GCP), CI/CD, and responsible AI practices, with opportunities to lead teams and influence ML tooling and processes.

Qualifications

• Bachelor’s degree required.
• 6+ years of experience designing and building data-intensive solutions.
• 4+ years of programming experience in Python, Scala, or Java.
• 2+ years of building, scaling, and optimizing ML systems.
• No sponsorship or immigration support.

Responsibilities

• Productionize ML applications and systems at scale.
• Participate in design, development, and implementation of ML applications.
• Focus on ML architectural design and review model and application code.
• Ensure high availability and performance of ML applications.
• Collaborate with Product and Data Science teams to deliver ML models and components.
• Leverage cloud platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines feeding ML models.
• Apply CI/CD, test automation, and monitoring for deployments.
• Manage code to govern models from a risk perspective and apply Responsible AI practices.

Skills

Distributed computing

Python/Scala/Java

ML systems design

CI/CD

Test automation

Data pipelines

Leadership

Agile teamwork

Education

Bachelor's degree

Master's or Doctoral degree

Tools

AWS

Azure

GCP

Scikit-learn

PyTorch

Dask

Spark

TensorFlow

Job description

• Productionize machine learning applications and systems at scale
• Participate in detailed technical design, development, and implementation of ML applications
• Focus on ML architectural design and develop and review model and application code
• Ensure high availability and performance of ML 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 with a cross-functional Agile team to create and enhance big data and ML applications
• 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 CI/CD practices, test automation, and monitoring for ML model and application deployments
• Manage code to reduce vulnerabilities, govern models from a risk perspective, and apply Responsible and Explainable AI best practices
• Contribute to the Marketing and Messaging team’s scalable platforms for hyper-personalized omnichannel messages and experiences

Requirements

• Bachelor’s Degree
• At least 6 years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems
• No employer sponsorship or immigration-related support for employment authorization
• Preferred: Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
• Preferred: 3+ years of experience building production-ready data pipelines that feed ML models
• Preferred: 3+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• Preferred: 2+ years of experience developing performant, resilient, and maintainable code
• Preferred: 2+ years of experience with data gathering and preparation for ML models
• Preferred: 2+ years of people leader experience
• Preferred: 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Preferred experience developing and deploying ML solutions in AWS, Azure, or Google Cloud Platform
• Preferred experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• Preferred ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents
• Preferred experience leveraging interactive AI tooling beyond basic code completion

Core Competencies

Demonstrates expertise in designing, building, and optimizing machine learning systems and data pipelines, with a strong focus on cloud-based architectures and CI/CD practices. Proven ability to collaborate with cross-functional teams to deliver high-performance ML applications that solve real-world business problems.

Highest-signal resume keywords

• Machine Learning System Design
• Python Programming
• Data Pipeline Development
• Cloud Platform Experience
• Agile Collaboration

Hard Skills

• Machine Learning
• Data Engineering
• Model Validation
• Hyperparameter Tuning
• Application Code Development
• CI/CD Practices
• Test Automation
• Distributed Computing
• Performance Optimization
• Data Gathering

Soft Skills

• Collaboration
• Leadership
• Communication

Industry Keywords

• Responsible AI
• Explainable AI
• Big Data
• Omnichannel Messaging
• Data-Intensive Solutions

Tools & Technologies

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