Key Responsibilities

1. Machine Learning Model Development

• 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.

2. Data Exploration & Analysis

• Conduct exploratory data analysis (EDA) to identify trends and insights.

• Translate data insights into recommendations for automation improvements.

3. Model Deployment & Optimization

• 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.

4. Cross-Functional Collaboration

• 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.

5. Research & Innovation

• 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.

6. Data Governance & Best Practices

• Ensure data integrity, security, and compliance.

• Maintain documentation of model development and deployment processes.

Qualifications

Education & Experience

• 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.

Technical Skills

• 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.

Preferred Qualifications

• 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.