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Company Details
Spector.ai is an AI-driven industrial asset health and reliability platform that helps organizations transform how they manage and maintain critical equipment. It uses generative AI, multi-modal AI agents, and machine learning to integrate live and historical data from diverse sources into a unified Asset Health Knowledge Graph, enabling predictive maintenance, automated visual inspection, and real-time actionable insights across the asset lifecycle. The platform supports proactive identification of failures and anomalies, prescriptive recommendations for maintenance actions, automated work order generation, and integration with existing enterprise systems (like CMMS/EAM), helping industries such as oil & gas, manufacturing, power and energy, and infrastructure improve uptime, reduce unplanned downtime and maintenance costs, and extend asset life. Spector.ais solutions are built to scale with industrial operations and provide a digital assistant experience that augments reliability engineers and maintenance teams, accelerating operational decision-making and boosting overall asset performance.
Job Roles & Responsibilities
- Develop AI models for industrial asset health using TensorFlow and PyTorch
- Implement predictive maintenance solutions for the Oil & Gas industry
- Enhance visual inspection processes for manufacturing sector using PyTorch
- Collaborate on AI agents to manage asset health in renewable energy
- Optimize model performance for industrial applications with TensorFlow expertise
- Maintain machine learning pipeline for predictive analytics in infrastructure
- Evaluate AI solutions for integration into chemical industry systems
- Analyze datasets to refine machine learning algorithms for power sector
Ideal candidate profile
- Thrives in a collaborative environment, leveraging TensorFlow to innovate solutions
- Displays adaptability, using PyTorch to tackle diverse challenges head-on
- Embraces change with immediate availability, ready to make an impact
Job ID: 145323187
Skills:
pruning , Tensorflow, MLops, Pytorch, Python, PEFT, Hugging Face, knowledge distillation, ONNX, LoRA, quantization, QLoRA
Skills:
Machine Learning, MLops, ML pipelines, Experiment tracking, Model versioning, Hyperparameter tuning
Skills:
data strategies , Machine Learning, training methodologies, data annotation, AI evaluation systems, data quality review, AI systems, LLM evaluation
Skills:
Tensorflow, Pytorch, Python, Docker, ML fundamentals, MLOps tools, Airflow, MLflow, distributed training, evaluation metrics, experiment tracking, ML pipelines, Weights Biases, Statistics, Optimization, architectures
Skills:
Api Development, AWS, Pytorch, FastAPI, Python, Docker, Flask, SpaCy, machine learning fundamentals, search and indexing systems, Langchain, MCP, Agentic AI, DSPy, Generative AI, LLM Evaluation, LangGraph
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