ML Engineer (Research)

Навыки

• AI-инструменты в работе
• Коммуникация
• Computer Vision
• Machine Learning
• NLP
• PyTorch
• Transformers / HuggingFace

Задачи

• Design and implement end-to-end training pipelines for state-of-the-art models in computer vision - video and image generative models
• Develop complex data pipelines to transform raw inputs (images, video, text, audio) into high-quality, annotated datasets that power model training and evaluation
• Work tightly with scrapping and annotation teams
• Optimize models for speed, scalability, and efficiency
• Develop tools and frameworks to accelerate training, evaluation, and deployment of large models
• Collaborate with product and design teams
• Beat other models on public benchmarks (e.g. LMArena, Artificial Analysis)
• YOUR MUST HAVES
• You don’t need to meet every single requirement to be a strong candidate — if you’re excellent in a few of these areas and eager to grow, we’d still love to hear from you
• Knowledge of modern ML research trends, frameworks, and tooling (e.g., PyTorch, Hugging Face, DeepSpeed, Accelerate, Ray)
• Experience with evaluation of complex ML systems
• Willingness to work in a fast-paced, high-intensity startup environment
• THE DEAL
• Competitive salary in USD
• On-site role in our Almaty office
• Full-time position with high growth potential
• WHY WORK AT HIGGSFIELD AI?
• Higgsfield AI is the fastest-growing GenAI platform in the world — #1 in Video AI in the U.S. and top globally by growth

Требования

• Proven track record of training and deploying ML models into production (experience with large-scale vision (especially diffusion models), NLP, or multimodal systems is a big plus)
• Strong skills in model training, optimization, and evaluation, with hands-on experience in distributed training and multi-GPU systems is a big plus
• Excellent communication skills and ability to collaborate across research, engineering, and product teams

Условия

• We raised a $130M Series A — and we’re only getting started
• This is your chance to join early, when the team is small but mighty, and help build the next GenAI decacorn

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