Applied AI Engineer

Overview

Company name: Applix AI | HQ Location: Austin, Texas | Website | LinkedIn

Role: Applied AI Engineer

• Salary: Rs. 25-50  lakhs per annum
• Experience: 2-8 years
• Location: Remote
• Type: Full-time

Key Responsibilities: 

1. Architect cutting-edge multi-modal AI systems that integrate text, image, and 3D CAD data to optimize manufacturing workflows and drive defect prevention. 
2. Develop advanced generative design and optimization algorithms leveraging AI to streamline product design and improve time-to-market. 
3. Implement federated learning to securely train models on client data while preserving IP protection and ensuring data never leaves the premises. 
4. Design robust transfer learning solutions to apply AI insights across multiple manufacturing domains and workflows. 
5. Optimize AI models for edge deployment, ensuring high performance in resource-constrained, real-time factory environments. 
6. Adapt state-of-the-art large language models (LLMs) to specialized engineering and manufacturing applications, enhancing collaboration and operational efficiency. 
7. Develop privacy-preserving machine learning techniques, ensuring data confidentiality in collaborative learning across industrial partners. 
8. Scale AI deployments across multi-cloud, on-premise, and edge systems with robust workload planning for security and scalability. 
9. Collaborate with domain experts to transform complex manufacturing challenges into actionable AI-driven insights and solutions. 

Requirements: 

1. Ranked in the top 1% globally in AI/ML community, with a proven track record of delivering breakthrough AI solutions. 
2. Deep experience in multi-modal AI architectures, fusing text, image, and 3D data in complex industrial environments. 
3. ⁠Expertise in federated learning systems for secure, distributed AI, with practical implementation experience. 
4. ⁠Strong background in transfer learning for cross-domain applications, particularly in manufacturing. 
5. Proficiency in edge AI optimization, deploying AI models in low-latency, resource-limited environments. 
6. ⁠Hands-on experience in fine-tuning LLMs for domain-specific applications, particularly in engineering and manufacturing contexts. 
7. Advanced knowledge in privacy-preserving AI techniques, including secure multi-party computation. 
8. 7+ years of experience deploying industrial-grade AI/ML systems in real-world production environments. 
9. Demonstrated success in publishing cutting-edge research in top AI conferences (NeurIPS, ICML, ICLR) focused on federated learning, transfer learning, or industrial AI. 
10. Advanced coding skills in Python, PyTorch, TensorFlow, and deep familiarity with federated learning frameworks. 

Preferred: 

1. Background in mechanical engineering, manufacturing, or related fields. 
2. Experience in reinforcement learning for process optimization and automation. 
3. Familiarity with Industry 4.0, IoT, and cybersecurity standards in manufacturing environments. 
4. ⁠Strong knowledge of manufacturing processes, CAD/CAM systems, and engineering principles. 

About us
Applix revolutionizes manufacturing with our AI Copilot, an intelligent assistant that optimizes designs, prevents defects, and slashes time-to-market and cost, while keeping humans in the loop. We blend cutting-edge technology with human expertise and Industry 4.0 consulting to drive unprecedented efficiency and quality. Our human-centric approach transforms manufacturing processes, establishing us as a go-to-partner in smart, sustainable solutions.