Develop ML models for predictive maintenance, anomaly detection, and process optimization.
Enhance robotic intelligence with ML for perception, navigation, SLAM, and sensor fusion.
Extract and engineer features from sensor data for model optimization.
Conduct exploratory data analysis (EDA) to identify trends and insights.
Translate data insights into recommendations for automation improvements.
Deploy ML models on cloud and edge platforms for real-time efficiency.
Optimize models for NVIDIA Jetson, ARM Cortex, and embedded AI hardware.
Continuously monitor and refine model performance using real-time data.
Develop high-quality data pipelines and align insights with business goals.
Integrate ML solutions into robotic systems and ensure operational alignment.
Present findings and support data-driven decision-making.
Stay updated on advancements in AI/ML, reinforcement learning, and generative AI.
Lead R&D projects in robotics, automation, and AI-driven systems.
Contribute to open-source projects and industry research.
Ensure data integrity, security, and compliance.
Maintain documentation of model development and deployment processes.
Master’s or Ph.D. in Data Science, AI, Machine Learning, or related fields.
3+ years of experience in data science, preferably in robotics or industrial automation.
Expertise in TensorFlow, PyTorch, Scikit-Learn, and deep learning frameworks.
Experience in supervised, unsupervised, and reinforcement learning.
Proficiency in Python, R, and preferably C++.
Knowledge of big data frameworks (Hadoop, Spark) and cloud platforms (AWS, Azure, GCP).
Familiarity with Docker, Kubernetes, and MLOps workflows.
Proficiency in Matplotlib, Seaborn, Tableau, and Power BI.
Experience with robotics, industrial IoT, and edge AI deployment.
Strong background in statistical modeling and Bayesian inference.
Contributions to open-source projects or research publications.