Senior ML/AI Engineer

🕒 6 days ago

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PulseRise Technologies

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2025

🤝 B2B

🎯 Recruiter

🔒 Cybersecurity

B2B • Recruitment • Cybersecurity

PulseRise Technologies is an international IT services and outstaffing firm that builds and manages remote tech teams for clients across EMEA, LATAM, and the USA. They provide staff and team augmentation, software and web development, cloud & DevOps engineering, multilingual technical support, cybersecurity services, and specialized staffing for FinTech and trading platforms, along with creative and UX/UI design studios and private-label mobile app development. PulseRise focuses on connecting IT professionals with companies to accelerate delivery, ensure regulatory compliance, and keep operations scalable and cost-efficient.

📋 Description

• Design, build, and deploy ML models for demand forecasting, time series prediction, consumer sentiment analysis, and anomaly detection at enterprise scale • Develop and iterate on the agentic AI architecture — building systems that reason across heterogeneous data sources and take autonomous action • Build and maintain robust ML pipelines: data preprocessing, feature engineering, model training, evaluation, and production deployment • Architect and improve the production graph RAG system • Build RAG systems and LLM integrations that power natural language interfaces and autonomous workflows • Collaborate with backend engineers to ensure models are production-grade — optimized for latency, reliability, and scale • Own model performance end-to-end: monitoring, retraining, and continuous improvement in production • Stay at the frontier of AI research and bring relevant innovations into the platform

🎯 Requirements

• 5+ years of experience in applied machine learning and AI • M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field — or equivalent practical experience • Deep proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow, scikit-learn) • Strong background in statistical analysis, predictive modeling, and time series forecasting • Experience with applied agentic AI/ML systems and multi-agent orchestration • Experience with NLP, LLMs, and RAG architectures • Comfort working with large-scale datasets and distributed computing environments • Nice to have Graph database or graph RAG experience (a major plus — core to the stack) • Background in retail, supply chain, or demand forecasting domains • Experience with graph neural networks or knowledge graphs • Familiarity with MLOps platforms and model serving infrastructure • Contributions to open-source ML/AI projects or published research

🏖️ Benefits

• High agency • Low ego • Great communicator