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Forward Deployed Machine Learning Engineer

OmegaHires
Contract
On-site
San Francisco, California, United States

Title: Forward Deployed Machine Learning Engineer
Job Type: Contract / FTE (W2 only)
Location: San Francisco, CA - Onsite/ Hybrid/ Remote

 

Role Overview

We’re seeking a high-agency Forward Deployed / Applied ML Engineer to bridge cutting-edge generative AI research with real-world production systems. You’ll work directly with customers to deploy, optimize, and customize our FLUX diffusion models across diverse environments, from on-prem GPU clusters to hosted infrastructure.
 

Key Responsibilities

Deploy and optimize FLUX diffusion models in customer environments, balancing latency, cost, and output quality

Architect deep product integrations beyond APIs, including model hosting, inference optimization, and production deployment
Fine-tune and customize foundation models for customer-specific visual media use cases
Lead technical deep dives with customers to diagnose model, infrastructure, and performance issues
Translate customer challenges into actionable engineering solutions and research feedback
Identify emerging industry use cases for generative visual AI
 

Required Qualifications

Hands-on experience deploying and serving generative AI / deep learning models in production
Strong expertise in diffusion models, model fine-tuning, optimization, and inference
Proven experience as an ML Engineer shipping models used by real systems
Strong Python skills and experience designing and consuming APIs
Ability to communicate complex ML tradeoffs to both technical and non-technical stakeholders
Experience working directly with customers on technical AI integrations
Know the FLUX ecosystem intimately—ComfyUI, common training frameworks, the tools practitioners actually use
 

Preferred Qualifications

Deep knowledge of diffusion models, flow matching, distillation, and advanced fine-tuning techniques
Experience optimizing inference for transformer-based models under real production constraints
Experience deploying models on cloud platforms with modern serving infrastructure
Background contributing to open-source ML / diffusion model projects
Experience designing solutions in constrained enterprise environments