AI Engineer

About LottieFiles Partner: We are partnering with a hyper-growth creative technology enterprise building next-generation AI-powered design automation suites, vector animation networks, and interactive media workflows. Operating at the highly applied intersection of generative model architectures and structured motion graphics, their platform empowers hundreds of thousands of digital creators to radically accelerate visual content production cycles through low-latency model adaptation and measurable quality feedback systems.

Position Overview

We are seeking a deeply technical, research-driven AI Engineer (R&D) to design, optimize, and scale domain-specific generation, editing, and self-correction systems for structured content pipelines. Moving far beyond basic prompt engineering wrappers, you will take absolute technical ownership of fine-tuning open-source foundational models to output syntax-accurate, structure-preserving animation data arrays. This track demands an infrastructure-focused engineer who can implement complex quantization layers, construct automated data cleansing pipelines from user retries, and establish deterministic evaluation benchmarks spanning compiler-aware AI runtimes.

Key Responsibilities

• Structured Generation & Fine-Tuning: Design and execute highly advanced parameter-efficient fine-tuning strategies leveraging LoRA, QLoRA, Supervised Fine-Tuning (SFT), and preference tuning to adapt models for targeted structural editing tasks.
• Model Optimization & Distillation: Experiment with cutting-edge open-source open weights including Llama, Qwen, Mistral, and DeepSeek to produce smaller, low-latency models optimized for self-correction and data routing.
• Data Factory Pipeline Construction: Build automated engineering data pipelines to collect, scrub, and promote successful model outputs, failures, and manual user retries into high-value training datasets.
• Objective Benchmarking & Observability: Develop measurable, automated evaluation criteria and tracking dashboards to audit model correctness, structural consistency, and runtime latency metrics.
• Orchestration & Self-Correction: Implement multi-step generation and autonomous repair workflows using intermediate representations and rendered vector outputs as feedback loops to correct code defects on the fly.
• Cross-Functional Alignment: Collaborate closely with downstream product squads, frontend creative teams, and design leads to drive uncompromised model deployment reliability.

Required Skills & Qualifications

• Demonstrated professional software engineering background developing structured LLM generation systems or shipping machine learning models inside applied research or production settings.
• Hands-on operational experience fine-tuning, training, or modifying open-source language topologies.
• Expert-level, production-grade systems programming proficiency utilizing Python.
• Strong, definitive command over prompt architecture, structure-constrained outputs, functional tool calling patterns, and core model failure analysis.
• Proven capacity to build automated evaluation frameworks, data scrubbing utilities, or scalable ML experimentation pipelines.
• Location Context: 100% remote-first global infrastructure flexibility requiring a minimum of **4 hours of active time overlap with the Malaysia timezone (MYT / UTC+8)**.
• Sponsorship: This direct-hire track does not offer international corporate visa sponsorship paths.

Preferred Strategic Indicators (Nice to Have)

• Direct production history with code generation, domain-specific language (DSL) structures, or compiler-aware program representations.
• Familiarity navigating web animation runtimes, vector graphics pipelines, design systems layout tools, SVG specs, WebGL architectures, or Abstract Syntax Trees (ASTs).
• Experience leveraging enterprise ML tracking and observability tooling infrastructures such as Weights & Biases, Langfuse, MLflow, or OpenTelemetry.

What We Offer

• The exceptional professional canvas to move beyond simple prompts and build production-grade AI infrastructure for next-generation interactive graphics.
• Highly competitive global salary package calibrated accurately based on your fine-tuning deployment history and code audit performance.
• 100% fully remote job freedom within a highly synchronized, engineering-first digital workspace.
• Direct collaboration with a highly technical, product-focused global team tackling challenging problems in multimodal AI systems reliability.