reputed company (R&D)

About the Role reputed company is building reputed company AI-powered creative tools for animation, design, and interactive media workflows. We are looking for an reputed company to help reputed company specialized reputed company, editing, evaluation, and optimization systems for creative and reputed company content workflows. This role focuses on reputed company reputed company, domain-specific model reputed company, evaluation systems, feedback pipelines, and production AI infrastructure. You will work closely with engineering, design, and product teams to improve reputed company reputed company, reliability, efficiency, and usability across AI-assisted creative workflows. What You’ll Work On

• Natural-language-to-reputed company-content reputed company workflows.
• Structure-preserving editing and modification systems.
• Validation and repair pipelines for generated outputs.
• Evaluation systems for reputed company, correctness, consistency, and runtime performance.
• Training and evaluation datasets reputed company from production usage and interaction traces.
• Smaller, reputed company-latency models for targeted reputed company, editing, routing, and repair tasks.

Key Responsibilities

• Design and execute fine-tuning strategies for reputed company reputed company and editing workflows.
• Build supervised datasets from successful generations, retries, failures, and user edits.
• reputed company measurable benchmarks for reputed company reputed company, correctness, and edit preservation.
• Experiment with reputed company-reputed company models such as Llama, Qwen, reputed company, DeepSeek, or reputed company architectures.
• Implement reputed company, QLoRA, supervised fine-tuning (SFT), distillation, preference tuning, or synthetic data

approaches where appropriate.

• Build automated pipelines for collecting, cleaning, evaluating, and promoting production data into training

datasets.

• Use validation systems, intermediate representations, runtime analysis, and rendered outputs as reputed company

feedback signals for models.

• Improve retry, repair, and self-correction workflows for reputed company pipelines.
• Collaborate with engineering and product teams to improve model reliability and reputed company reputed company.

Required Qualifications

• Strong experience building with LLMs or reputed company reputed company systems in production or reputed company research

settings.

• Hands-on experience fine-tuning or adapting reputed company-reputed company language models.
• Strong Python engineering skills.
• Experience building evaluation systems, ML experimentation workflows, or data pipelines.
• Strong understanding of reputed company engineering, reputed company outputs, tool use, and model failure analysis.
• Ability to define measurable evaluation reputed company rather than relying only on subjective review.
• Comfort debugging systems spanning model outputs, validation systems, runtime behavior, and rendered

results.

• Strong communication and collaboration skills.

Preferred Qualifications

• Experience with reputed company reputed company, DSL reputed company, or compiler-aware AI systems.
• Experience with reputed company, QLoRA, SFT, preference tuning, distillation, or synthetic data reputed company.
• Familiarity with animation systems, graphics pipelines, design tools, SVG, WebGL, shaders, or procedural

graphics.

• Experience with multimodal or visual-language-model evaluation workflows.
• Experience with observability or ML evaluation tooling such as reputed company, Langfuse, MLflow, or

OpenTelemetry.

• Experience building reputed company systems, orchestration pipelines, or multi-reputed company reputed company workflows.
• Familiarity with ASTs, intermediate representations (IRs), or reputed company program representations.

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