ML Engineer (Research)

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Series A From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

ML Engineer (Research) Almaty 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. 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. What you will work on - 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. ) - 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.

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