Machine Learning Infrastructure / MLOps Engineer

Overview

On Site
Full Time
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - Term Contract

Skills

Docker
Kubernetes
EC2
data governance
TensorFlow
PyTorch
MLOps
Generative AI
Data architecture
Cross-Functional Collaboration
Kubeflow
deep learning
Large Language Models (LLMs)
data security
Model lifecycle management
Data ingestion
Workflow automation
Model Deployment
ML Pipelines
Feature Engineering
Streaming Architectures
Artificial Intelligence (AI)
Machine Learning (ML)
Natural Language Processing (NLP)
AWS SageMaker
MLflow
BERT
Model Training
Model Inference
Model Optimization
Distributed Training
ML Infrastructure
End-to-End ML Systems
CI/CD for ML
ML Observability
Feature Store
ML Governance
Infrastructure as Code (IaC)
ML Monitoring
Data/Model Lineage
EKS
AWS Inferentia
AWS Trainium
Azure ML / GCP
ONNX
vLLM
Neuron Compiler
Ray
Real-time Data Pipelines
Batch Processing
Data Engineering Collaboration

Job Details

Solution IT Inc. is looking for a Machine Learning Infrastructure / MLOps Engineer for one of its clients Chicago, IL Hybrid

Job Title: Machine Learning Infrastructure / MLOps Engineer

Summary

Client seeks an experienced Machine Learning Engineer contractor to build algorithmic assets across Personalization, Generative AI, Forecasting, and Decision Science domains. This role combines deep technical modeling expertise with infrastructure engineering to design, build, and operate end-to-end ML/AI systems at scale.You'll implement foundational MLOps frameworks across the full product lifecycle including data ingestion, ML processing, and results delivery/activation. Working cross-functionally with data science, data engineering, and architecture teams, you'll serve as both solutions architect and hands-on implementation engineer.

Required Skills

  • Model Development & Optimization
    • Design and optimize machine learning models including deep learning architectures, LLMs, and specialized models (BERT-based classifiers)
    • Implement distributed training workflows using PyTorch and other frameworks
    • Fine-tune large language models and optimize inference performance using compilation tools (Neuron compiler, ONNX, vLLM)
    • Optimize models for hardware targets (GPU, TPU, AWS Inferentia/Trainium)
  • Infrastructure Design & AI-Services Architecture
    • Design AI-services and architectures for real-time streaming and offline batch optimization use-cases
    • Lead ML infrastructure implementation including data ingestion pipelines, feature processing, model training, and serving environments
    • Build scalable inference systems for real-time and batch predictions
    • Deploy models across compute environments (EC2, EKS, SageMaker, specialized inference chips)
  • MLOps Platform & Pipeline Automation
    • Implement and maintain MLOps platform including Feature Store, ML Observability, ML Governance, Training and Deployment pipelines
    • Create automated workflows for model training, evaluation, and deployment using infrastructure-as-code
    • Build MLOps tooling that abstracts complex engineering tasks for data science teams
    • Implement CI/CD pipelines for model artifacts and infrastructure components
  • Performance & Cross-functional Partnership
    • Monitor and optimize ML systems for performance, accuracy, latency, and cost
    • Conduct performance profiling and implement observability solutions across the ML stack
    • Partner with data engineering to ensure optimal data delivery format/cadence
    • Collaborate with data architecture, governance, and security teams to meet required standards
    • Provide technical guidance on modeling techniques and infrastructure best practices

Work Site: Chicago, IL - Hybrid

Duration: Long Term

Expected Start Date: Immediate - 2 weeks

Number of Positions: 01

Please send your responses back to

About Solution IT

Solution IT is a national IT consulting company specializing in: Technology Staffing and Oracle E-Business Solutions based in Boston, Massachusetts.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.