Member of Technical Staff, Senior Applied AI Engineer, Image Generation

Microsoft•Redmond, WA

About The Position

We’re hiring a Senior Applied AI Engineer, Image Generation to join a fast‑moving, high‑ownership team building next‑generation AI assistant and productivity capabilities. This role blends LLM product engineering, evaluation science, hillclimbing, and internal tool building with the pace and creativity of a startup. The primary focus for this role will be on building the best image generation product out there. You'll get to experiment with all sorts of models from open source to SOTA developed at Microsoft. You'll work through some of the most challenging multimodal problems that exist today while shipping improvements to customers daily.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Nice To Haves

Master’s Degree AND 3+ years of experience in engineering, problem solving, model building, evaluation, data analysis OR equivalent experience.
PhD in engineering, applied math, statistics, or related analytical field.
2+ years shipping production-level code, models, or data analysis.
1+ years using AI-assisted coding and analysis techniques.
Solid grasp of deep learning: loss functions, optimization, regularization, training stability
Experience deploying ML models at scale (inference optimization, quantization, distillation)
Familiarity with image preprocessing pipelines, data augmentation, and dataset curation
Experience working on small teams and mid-stage startup environments.
Experience working on AI products.
4+ years shipping production-level code, models, or data analysis.
Deep experience building from zero-to-one.
Experience with RLHF / DPO for aligning image models to human preferences
Knowledge of safety/content filtering for generated images
Hands on work hillclimbing AI evaluations.

Responsibilities

Model Development & Training
Train, fine-tune, and evaluate image generation models (diffusion, GAN, transformer-based)
Implement and adapt techniques from research papers into working production systems
Design and run experiments to improve image quality, diversity, and controllability
Curate, clean, and manage large-scale image-text training datasets
Evaluation, Hillclimbing & Quality Systems
Build and maintain evaluation frameworks for correctness, safety, grounding, and UX quality.
Run hillclimbing loops across prompts, models, and tool‑use strategies to continuously improve assistant performance.
Analyze failure modes, design mitigations, and drive systematic improvements across the stack.
LLM Tooling & Internal Infrastructure
Develop internal tools for prompt experimentation, model comparison telemetry and debugging automated eval pipelines
Create reusable frameworks that accelerate the entire AI org’s ability to ship high‑quality assistant features.
Applied ML & Product Integration
Integrate LLMs with product surfaces, APIs, and backend systems.
Build lightweight ML components (ranking, classification, summarization, personalization) that enhance assistant intelligence.
Collaborate with PM, design, and research to turn ambiguous ideas into polished user experiences.
High‑Velocity Teamwork
Operate with startup‑founder energy: bias for action, rapid iteration, and comfort with ambiguity.
Work closely with researchers, engineers, and product leaders in a fast-moving AI team where ideas ship quickly and impact is immediate.
Contribute to a culture of experimentation, clarity, and high‑quality execution.
Build prompt architectures, system instructions, and orchestration logic that ensure reliability, grounding, and personality consistency.
Prototype new capabilities rapidly and iterate based on user signals and evaluation data.
Production & Infrastructure
Optimize models for inference latency, throughput, and cost (quantization, distillation, batching)
Build and maintain serving pipelines for real-time and batch image generation
Develop APIs and SDKs that expose image generation capabilities to downstream teams/products
Monitor model performance in production; debug quality regressions