Vinayaka Steels, Surana Group, Grant Thornton - AI/ML Engineer II

Can you harness the power of AI to predict and prevent breakdowns before they disrupt operations? We are seeking an innovative AI/ML Engineer II to develop predictive maintenance solutions that redefine reliability, efficiency, and asset performance across industries.

Your Mission:

• Architect Predictive Models: Develop state-of-the-art ML models for failure prediction, leveraging techniques like time-series analysis, anomaly detection, and Bayesian optimization.
• Seamless IoT Integration: Design solutions that integrate with IoT ecosystems, collecting and analyzing sensor data in real time to anticipate maintenance needs.
• Optimize Maintenance Strategies: Build intelligent systems to minimize downtime, reduce costs, and extend equipment lifecycles through data-driven scheduling.
• Scalable AI Pipelines: Design and deploy robust pipelines capable of handling large-scale, high-velocity data streams, ensuring reliable and scalable solutions.
• Insights and Automation: Transform raw data into actionable insights using advanced analytics and automation tools to empower decision-makers.

What Were Looking For:

• Expertise in Advanced ML: Strong experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn, and a deep understanding of unsupervised learning, clustering, and time-series forecasting techniques.
• Data Engineering Skills: Proficiency in working with real-time data processing tools like Apache Kafka, Spark, or Flink, and familiarity with databases like Snowflake, DynamoDB, or PostgreSQL.
• IoT and Edge Computing: Hands-on experience with IoT platforms and edge computing frameworks, ensuring low-latency, real-time predictions in distributed environments.
• Cloud Computing: Expertise in cloud ecosystems such as AWS (IoT Core, SageMaker), GCP, or Azure, with a focus on scaling and deploying AI models.
• Strong Programming Skills: Advanced proficiency in Python, with additional skills in C++, or R being a plus.
• Domain Knowledge: Familiarity with maintenance workflows, CMMS systems, and industrial protocols (e.g., MQTT, OPC-UA) is highly desirable.

What Youll Achieve:

• Build next-generation maintenance systems that reduce unplanned downtime by up to 30%.
• Enable clients to transition from reactive to predictive maintenance models, ensuring greater efficiency and reliability.
• Develop solutions that seamlessly scale across industrial assets, from factories to energy grids.

Join us in shaping the future of industrial resilience and operational excellence through AI.