Designs, fine-tunes, and deploys image generation models for photorealistic AI bots, optimizing for consistency, latency, and quality. Requires 5+ years software engineering, 2+ years production ML, and expertise in diffusion models like Stable Diffusion and PyTorch.
200k – 265k/yr
Remote5+ YOEML Engineering
About the role
What You’ll Do
Evaluate new image generation and identity preservation papers and models
Develop and deploy new versions of the image generation and image analysis pipelines
Monitor and fix production issues that impact users
Fine-tune and optimize models to improve character consistency, prompt responsiveness, and inference latency
Design and run experiments to benchmark model performance, tracking quality metrics across generations of pipeline improvements
Collaborate with cross-functional teams to translate product requirements into ML solutions and bring new generative features from prototype to production
What You’ll Bring
Demonstrated interest in AI image generation (personal and professional projects)
Deep technical foundation in machine learning specifically in image synthesis
5+ years experience as a software engineer, preferably in services
2+ years of experience building production-grade machine learning models in industry and/or academic research settings
Strong programming skills in Python and deploying Python based services
Familiarity with tools and frameworks involved in AI image generation including but not limited to Stable Diffusion, Diffusion Transformers (DiT), Visual Transformers (ViT), Tensorflow, PyTorch, Diffusers, ComfyUI, TensorRT, and CUDA
Experience building end-to-end scalable ML infrastructure with on-premise or cloud platforms including Baseten, Google Cloud Platform (GCP), Amazon Web Services (AWS) or Azure
Strong teamwork skills including communication and collaboration with both technical and non-technical team members
Compensation
Anticipated annual base salary range: $200,000-$265,000
Research Engineer building self-improving AI agent systems at Console. Develop eval/optimization loops, fine-tune specialist models, and improve agent reasoning over enterprise context using production data to drive measurable gains in quality, latency, and reliability.
200k – 350k/yr
On-siteML Engineering
Machine Learning Engineer
KeplerNew York, NY
Build and own ML models, fine-tuning, evaluation harnesses, and routing for Kepler's AI agent harness in finance. Requires 5+ years production software experience and shipped ML systems focused on correctness, evals, and real-world reliability.
200k – 280k/yr
On-site5+ YOEML Engineering
Machine Learning Engineer
AfterQuerySan Francisco, CA
Build production ML systems for measuring, predicting, and scaling data quality for frontier AI models. Requires 3-6 years experience in applied ML or related production systems (ranking, recommendations, data quality, fraud) plus strong software engineering skills.
200k – 300k/yr
On-site3+ YOEML Engineering
Machine-Learning Operations Engineer
TennrNew York, NY
Founding ML Operations Engineer building scalable training, inference, and evaluation pipelines for proprietary VLMs and LLMs in healthcare. Requires 5+ years production ML infrastructure experience, strong Python/TypeScript skills, and ownership in a fast-paced startup.
200k – 230k/yr
On-site5+ YOEML Engineering
Machine Learning Engineer, Enterprise Brain
GleanMountain View, CA
Machine Learning Engineer building the Enterprise Brain - a proactive AI system for task detection, automation, reasoning, planning and personalization using LLMs, RL, fine-tuning, and advanced ranking on top of enterprise and personal knowledge graphs. Requires 3+ years ML experience, strong production ML skills, and expertise in evaluation/benchmarking.