Senior Applied ML Engineer

Навыки

• AI-инструменты в работе
• Computer Vision
• Форензика и реагирование
• Machine Learning
• Ответственность за результат
• Python
• PyTorch

О компании и продукте

• We are looking for a Senior Applied Machine Learning Engineer to build and own production ML systems for content understanding, moderation, and policy enforcement across AI-generated images and video.
• You will work on applied problems such as:
• Content moderation including: NSFW detection, intellectual property and character recognition, policy violation detection, content classification, and other trust and safety use cases.
• User behavior prediction / segmentation.

Задачи

• Own applied ML projects end to end, from problem definition and data collection to production deployment and monitoring
• Build multimodal classification and detection systems for images, video, text, and metadata
• Develop solutions for NSFW detection, intellectual property and character recognition, content policy enforcement, and related trust and safety use cases
• Fine-tune and evaluate vision-language models, classifiers, embedding models, and other relevant architectures
• Build high-quality training and evaluation datasets using human labeling, synthetic data, hard-negative mining, and active learning
• Define evaluation frameworks that reflect real production scenarios rather than relying only on standard offline benchmarks
• Design and optimize inference pipelines for high throughput, low latency, reliability, and cost efficiency
• Establish production monitoring for model quality, data drift, policy coverage, false positives, and false negatives
• Run experiments and analyze the impact of ML systems on user experience, platform safety, conversion, retention, generation success rate, and operational costs
• Work closely with Product, Engineering, Legal, Policy, and Operations teams to translate business and policy requirements into scalable technical systems
• Make pragmatic build-versus-buy decisions and combine internal models, third-party solutions, and rule-based systems where appropriate
• Contribute to the architecture and technical direction of the company’s applied ML platform
• WHY WORK AT HIGGSFIELD AI?

Требования

• 5+ years of experience in machine learning, with significant experience deploying ML systems into production
• Strong experience with computer vision, multimodal machine learning, content understanding, recommendation, ranking, fraud detection, trust and safety, or a related applied ML domain
• Proven ability to independently own complex ML projects from an ambiguous business problem through production launch
• Strong understanding of model evaluation, including precision and recall trade-offs, threshold selection, calibration, class imbalance, and cost-sensitive decision-making
• Experience building datasets, labeling workflows, evaluation sets, and feedback loops for continuously improving model quality
• Experience deploying and operating models at scale, including inference optimization, monitoring, retraining, and incident response
• Strong Python skills and experience with modern ML frameworks such as PyTorch
• Ability to work with large-scale data and production systems
• Strong product judgment and an understanding of how model performance connects to user experience and business outcomes
• Ability to communicate technical trade-offs clearly to both technical and non-technical stakeholders
• PRODUCTION METRICS YOU MAY OWN
• Precision and recall across different content and policy categories
• False-positive rates and the percentage of legitimate user generations incorrectly blocked
• False-negative rates and exposure to policy-violating content
• User appeal and moderation reversal rates
• Generation success and completion rates
• Model inference latency and system availability
• Cost per classification or generation
• Manual review volume and operational workload
• Coverage across new models, formats, markets, and policy categories
• Impact on user retention, engagement, and conversion

Будет плюсом

• Experience with trust and safety, content moderation, copyright or intellectual property detection
• Experience working with generative image or video models
• Experience with vision-language models, embeddings, similarity search, perceptual hashing, or retrieval systems
• Experience building human-in-the-loop review and annotation systems
• Familiarity with adversarial behavior, model evasion, abuse patterns, and continuously changing content distributions
• Experience in a fast-moving startup environment
• WHAT SUCCESS LOOKS LIKE
• Within your first months, you will independently take ownership of a high-impact applied ML problem, establish a reliable evaluation baseline, deploy an initial production solution, and create a measurable improvement loop based on real user and business outcomes
• Over time, you will help build a scalable content intelligence and trust and safety platform that supports new models, products, policies, and markets without creating unnecessary friction for legitimate users

Условия

• Competitive base salary in USD
• Equity: participation in the company’s stock option program, giving you the opportunity to share in the company’s long-term growth
• On-site role in our Almaty office (we will relocate you from anywhere)
• Higgsfield 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

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