Principal AI/ML Engineer

Jobtailor; New York (NY); On-site; USD 180,000 - 260,000; Full time

Job summary

Jobtailor in New York seeks an experienced AI Architect to design, develop, and optimize machine learning and deep learning models for production systems. You will research state-of-the-art methodologies including LLMs, transformers, and reinforcement learning to drive innovation and model efficiency.

You will lead AI strategy, build scalable training and inference pipelines, and collaborate with engineering, data, and product teams to integrate AI/ML into business solutions while ensuring

Qualifications

• 8+ years of experience in AI/ML, deep learning, or applied AI
• Expertise in Python and ML frameworks including TensorFlow, PyTorch, JAX, and Hugging Face Transformers
• Strong background in computer vision, NLP, generative AI, or reinforcement learning
• Experience developing scalable AI pipelines, data processing workflows, and distributed training systems
• Familiarity with big data tools including Apache Spark, Kafka, and Hadoop
• Familiarity with MLOps platforms including MLflow, TFX, and SageMaker
• Deep understanding of LLMs, transformer architectures, and retrieval-augmented generation (RAG) pipelines
• Experience with model quantization, fine-tuning, and performance optimization
• Strong knowledge of AWS, GCP, Azure, Docker, and Kubernetes
• Track record of technical leadership, mentoring, and driving AI innovation
• LinkedIn URL and resume/CV required for the Talent Network submission

Responsibilities

• Architect, develop, and optimize machine learning and deep learning models for production systems
• Research and apply state-of-the-art AI methodologies, including LLMs, transformers, and reinforcement learning
• Lead AI strategy by identifying opportunities for innovation and model optimization
• Develop scalable training and inference pipelines for AI-powered applications
• Work closely with engineering, data, and product teams to integrate AI/ML into business solutions
• Optimize ML models for efficiency, accuracy, and scalability in real-world deployments
• Ensure robust MLOps practices, including model monitoring, retraining, and deployment automation
• Collaborate on AI/ML research publications, patents, and open-source contributions

Skills

Machine Learning

Deep Learning

NLP

Computer Vision

Reinforcement Learning

Python

Tools

TensorFlow

PyTorch

JAX

Hugging Face Transformers

Apache Spark

Kafka

Hadoop

MLflow

TFX

SageMaker

AWS

GCP

Azure

Docker

Kubernetes

Job description

• Architect, develop, and optimize machine learning and deep learning models for production systems
• Research and apply state-of-the-art AI methodologies, including LLMs, transformers, and reinforcement learning
• Lead AI strategy by identifying opportunities for innovation and model optimization
• Develop scalable training and inference pipelines for AI-powered applications
• Work closely with engineering, data, and product teams to integrate AI/ML into business solutions
• Optimize ML models for efficiency, accuracy, and scalability in real-world deployments
• Ensure robust MLOps practices, including model monitoring, retraining, and deployment automation
• Collaborate on AI/ML research publications, patents, and open-source contributions

Requirements

• 8+ years of experience in AI/ML, deep learning, or applied AI
• Expertise in Python and ML frameworks including TensorFlow, PyTorch, JAX, and Hugging Face Transformers
• Strong background in computer vision, NLP, generative AI, or reinforcement learning
• Experience developing scalable AI pipelines, data processing workflows, and distributed training systems
• Familiarity with big data tools including Apache Spark, Kafka, and Hadoop
• Familiarity with MLOps platforms including MLflow, TFX, and SageMaker
• Deep understanding of LLMs, transformer architectures, and retrieval-augmented generation (RAG) pipelines
• Experience with model quantization, fine-tuning, and performance optimization
• Strong knowledge of AWS, GCP, Azure, Docker, and Kubernetes
• Track record of technical leadership, mentoring, and driving AI innovation
• LinkedIn URL and resume/CV required for the Talent Network submission

Core Competencies

Demonstrates expertise in architecting and optimizing machine learning and deep learning models, with a strong focus on developing scalable AI pipelines and implementing robust MLOps practices. Proven ability to lead AI strategy and collaborate effectively with cross-functional teams to drive innovation.

Highest-signal resume keywords

• Machine Learning Model Optimization
• Deep Learning Expertise
• Python Programming
• MLOps Practices
• AI Strategy Leadership

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Deep Learning
• Computer Vision
• Natural Language Processing
• Generative AI
• Reinforcement Learning
• Model Quantization
• Performance Optimization
• Data Processing Workflows
• Distributed Training Systems

Soft Skills

• Technical Leadership
• Mentoring
• Collaboration

Industry Keywords

• AI Methodologies
• LLMs
• Transformers
• Retrieval-Augmented Generation
• Cloud Platforms
• AWS
• GCP
• Azure
• Docker
• Kubernetes

Tools & Technologies

• TensorFlow
• PyTorch
• JAX
• Hugging Face Transformers
• Apache Spark
• Kafka
• Hadoop
• MLflow
• TFX
• SageMaker