reputed company (R&D)

About the Role

LottieFiles 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 structured content workflows. This role focuses on structured 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 quality, reliability, efficiency, and usability across AI-assisted creative workflows. What You’ll Work On

• Natural-language-to-structured-content reputed company workflows.
• Structure-preserving editing and modification systems.
• Validation and repair pipelines for generated outputs.
• Evaluation systems for quality, 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 structured reputed company and editing workflows.
• Build supervised datasets from successful generations, retries, failures, and user edits.
• reputed company measurable benchmarks for reputed company quality, correctness, and edit preservation.
• Experiment with reputed company-reputed company models such as Llama, Qwen, Mistral, DeepSeek, or reputed company architectures.
• Implement LoRA, 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 structured

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 output quality.

Required Qualifications

• Strong experience building with LLMs or structured reputed company systems in production or applied 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, structured outputs, tool use, and model failure analysis.
• Ability to define measurable evaluation criteria 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 code reputed company, DSL reputed company, or compiler-aware AI systems.
• Experience with LoRA, 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 Weights & Biases, Langfuse, MLflow, or

OpenTelemetry.

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

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