Senior AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and enhance generative systems for AI-driven motion that translates natural language input.

• Refine prompt understanding, model orchestration, routing, retrieval, tool utilization, structured generation, validation, correction, and visual verification.

• Identify recurring failure patterns and execute sustainable improvements in prompts, data, system logic, constraints, or evaluation processes.

• Establish compiler-backed feedback mechanisms and deterministic quality control measures.

• Design experiments and consistent evaluation frameworks to assess improvements in output quality.

• Create supervised fine-tuning datasets, training methodologies, and post-training experiments specifically for Motion DSL generation.

• Investigate techniques such as distillation, preference optimization, synthetic data generation, reinforcement learning strategies, and constrained generation.

• Choose model checkpoints based on assessments of accuracy, visual quality, reliability, latency, and cost.

• Evaluate whether model failures should be resolved through data adjustments, training, inference, evaluation, or language/runtime considerations.

• Transform production outputs into training and evaluation datasets through filtering, provenance tracking, version control, deduplication, and contamination safeguards.

• Develop training, validation, and evaluation splits that minimize data leakage and ensure meaningful generalization assessments.

• Formulate failure taxonomies, hard negatives, regression test suites, and representative prompt collections.

• Integrate deterministic checks, model-based judges, render evidence, and human assessments into a robust evaluation framework.

• Manage the engineering process from start to finish with quantifiable impacts on the product.

⛳️ Requirements

• Extensive experience in machine learning and software engineering.

• Experience in building and maintaining production-grade AI or machine learning systems, beyond just prototypes.

• Proficient in working across model behavior, data pipelines, APIs, infrastructure, evaluation, and product code.

• Hands-on experience with supervised fine-tuning and contemporary post-training methodologies.

• Insight into how dataset construction influences model behavior.

• Capability to avert leakage, contamination, and inaccurate evaluation results.

• Proficient in designing experiments, regression test suites, automated grading systems, and evaluation datasets.

• Relevant experience with code generation models, domain-specific languages (DSLs), grammars, parsers, compilers, structured outputs, constrained decoding, or program synthesis is particularly pertinent.

• Production engineering acumen encompassing observability, reliability, latency, inference costs, caching, failure recovery, and maintainability.

• Experience in animation, motion design, graphics, creative tools, or multimodal systems is advantageous but not mandatory.

• Nice to have: familiarity with fine-tuning or evaluating code generation models.

• Nice to have: experience with multimodal or vision-language models.

• Nice to have: experience in developing model-based, human-in-the-loop, or rubric-driven evaluation systems.

• Nice to have: expertise in compilers, interpreters, language tooling, or program analysis.

• Nice to have: proficiency in Rust, PyTorch, or distributed training infrastructure.

• Nice to have: experience with preference optimization, reinforcement learning, or synthetic data pipelines.

• Nice to have: background in animation, graphics, rendering, or creative software.

🏝️ Benefits

• Fully Remote Working Environment

• Flexible Work Hours

• A welcome gift and LottieFiles swag pack

• Bonus to set up your workstation at home

• Unlimited Leave Days

• Medical Insurance

• Generous learning budget

• Gym membership

• Co-working space membership