{"slug": "ml-engineer-data-engine-higgsfield", "title": "ML Engineer (Data Engine) — Higgsfield", "summary": "Higgsfield AI, a generative AI company with $500M in annual revenue run rate and 25M+ users, is hiring an on-site ML Engineer (Data Engine) in Almaty, Kazakhstan, to analyze video motion, train reward models, and build video classifiers. The role involves developing multi-shot video sequences, audio processing, and large-scale data curation pipelines, with requirements including strong PyTorch skills and video-processing expertise.", "body_md": "# ML Engineer (Data Engine)\n\n- Salary\n- Not published\n- Location\n- Almaty, Kazakhstan\n- Work type\n- On-site\n- Posted\n- today\n\n[Apply on company site (opens in new tab)](https://jobs.ashbyhq.com/higgsfieldai/8a8d1931-6a2e-48f8-bbe0-770108a47028/application)\n\nWhy work at Higgsfield AI?\n\nHiggsfield AI is the fastest-scaling generative AI company in history, hitting $500M in annual revenue run rate, 25M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like.\n\nWhat you’ll do\n\n- Analyze motion and physical dynamics in video, including optical flow, camera vs. object motion, temporal consistency, and physical plausibility such as dynamics, collisions, gravity, and deformation.\n- Train models that will be used in post-training, including reward models.\n- Build video classifiers for motion types, shot types, genres, and quality, using both classical approaches and VLM/embedding-based methods.\n- Develop methods for creating multi-shot video sequences: shot-boundary detection, assembling coherent multi-shot sequences with consistent characters and scenes, and generating captions for individual shots.\n- Work with audio: speech/music/sound-event detection, audio-visual synchronization evaluation (lip-sync and sound-to-action alignment), audio-quality filtering, and audio-track captioning.\n- Apply classical and learned data-curation techniques, including near-duplicate detection, heuristic filtering, VLM-based captioning, synthetic data generation, and dataset versioning.\n- Build and run large-scale distributed processing pipelines.\n\nRequirements\n\n- Strong PyTorch skills and hands-on model training experience, including fine-tuning and deploying classifiers, embedding models, and VLMs.\n- Deep knowledge of video-processing methods, including motion analysis (optical flow, tracking, camera-motion estimation), shot-boundary detection, and temporal consistency and quality evaluation.\n- Experience building and validating classifiers on video data, including annotation workflows, active learning, threshold calibration, and precision/recall measurement at scale.\n- Strong understanding of data-curation techniques such as deduplication, filtering, sampling, and dataset balancing, as well as how these choices affect model training.\n- Experience processing large-scale unstructured datasets, particularly video, audio, and images.\n\nWhat We Offer\n\n- Competitive base salary in USD, based on your experience, skills, and the scope of the role.\n- Equity participation through the company’s stock option program, giving you the opportunity to share in Higgsfield’s long-term growth.\n- Relocation support to Almaty for candidates moving from another city or country.\n- A highly collaborative, fast-paced environment where you can work directly with experienced leaders and have a meaningful impact on the product and company.\n- Opportunities for professional growth, ownership, and career development as the company scales.\n- Company-provided equipment, meals, transportation, or other office benefits.\n\nThis is a fully on-site role based in our Almaty office. Our team works from the office five days per week for the full working day. We believe in-person collaboration is an important part of how we move quickly, solve complex problems, and build strong teams.", "url": "https://wpnews.pro/news/ml-engineer-data-engine-higgsfield", "canonical_source": "https://frontierroles.com/jobs/higgsfieldai-ml-engineer-data-engine-911ec8/", "published_at": "2026-08-24 06:17:41+00:00", "updated_at": "2026-08-25 03:44:27.409086+00:00", "lang": "en", "topics": ["machine-learning", "computer-vision", "generative-ai", "ai-infrastructure"], "entities": ["Higgsfield AI", "Almaty"], "alternates": {"html": "https://wpnews.pro/news/ml-engineer-data-engine-higgsfield", "markdown": "https://wpnews.pro/news/ml-engineer-data-engine-higgsfield.md", "text": "https://wpnews.pro/news/ml-engineer-data-engine-higgsfield.txt", "jsonld": "https://wpnews.pro/news/ml-engineer-data-engine-higgsfield.jsonld"}}