We are looking for a technically strong Machine Learning Engineer with 3–5 years of experience building and deploying production-ready ML models.
You will work on AI-powered spatial intelligence solutions that combine camera, Wi-Fi, BLE, and IoT data to help airports, factories, and enterprises understand their physical environments in real time.
What you’ll do:
• Transform complex business needs into well-defined ML problems
• Build models for classification, forecasting, clustering, anomaly detection, and time-series analysis
• Clean and transform real-world sensor and video data
• Deploy, monitor, and retrain models in production
• Create visualizations that clearly explain data quality and model behavior
What we’re looking for:
• Strong Python skills: NumPy, pandas, scikit-learn, PyTorch, or TensorFlow
• Solid foundations in statistics, probability, linear algebra, and optimization
• Experience with MongoDB, Kafka, and streaming data pipelines
• Practical MLOps experience: Docker, CI/CD, experiment tracking, and model monitoring
• Strong problem-solving and debugging skills
• Ability to explain model choices, trade-offs, and limitations
Experience in manufacturing analytics is a strong advantage, particularly with OEE, predictive maintenance, production forecasting, equipment alarms, MES, SCADA, PLCs, or industrial historians.
Nice to have:
• Agentic workflows and multi-agent systems
• LLM and RAG pipelines
• Computer vision
• AWS, Azure, or Google Cloud
• Kubernetes and edge deployment
💰 Compensation: USD 4,000–5,000 per month, depending on experience.
Interested or know someone who could be a great fit? Send us your résumé via direct message or tag the right person in the comments.
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