Senior AI Engineer

About Applix
Applix is transforming the future of manufacturing through AI, automation, and intelligent digital platforms. We build next-generation Manufacturing & Supply Digital Platforms that connect people, processes, machines, and data to enable smarter, faster, and more efficient industrial operations.
Our platform serves as the digital backbone of modern manufacturing—integrating engineering, production, quality, supply chain, and operational intelligence into a unified ecosystem. Leveraging cutting-edge technologies including Generative AI, NVIDIA Omniverse, Digital Twins, AWS AI/ML, and Agentic AI, we help enterprises accelerate innovation, improve operational efficiency, and enable data-driven decision making.
Role Overview
We are looking for an experienced Senior AI Engineer to design, develop, and deploy enterprise-scale AI and Generative AI solutions for manufacturing and supply chain platforms. The ideal candidate will have deep expertise in modern AI frameworks, production ML systems, LLMs, Agentic AI, and AWS AI services while working closely with cross-functional engineering teams to build scalable, high-performance AI applications.
This role involves developing intelligent automation solutions, optimizing large AI models for production, building digital twin capabilities, and enabling advanced analytics across manufacturing operations.
Key Responsibilities
Design, develop, and deploy production-grade AI and Generative AI applications.
Build and fine-tune Large Language Models (LLMs), Transformer models, diffusion models, GPT, BERT, and other foundation models for enterprise use cases.
Develop intelligent AI solutions for manufacturing process optimization, predictive maintenance, anomaly detection, quality control, and operational analytics.
Design and implement Agentic AI systems using frameworks such as LangChain, AutoGen, CrewAI, or similar technologies.
Build scalable RAG (Retrieval-Augmented Generation) architectures and enterprise AI workflows.
Develop and maintain synthetic data generation pipelines using sensor data, simulation environments, and virtual manufacturing scenarios.
Optimize AI models through quantization, pruning, compilation, and hardware-specific acceleration techniques for low-latency inference.
Perform benchmarking, profiling, debugging, and performance optimization of AI models and inference pipelines.
Build automated ML pipelines leveraging MLOps best practices, CI/CD, Docker, MLflow, and model lifecycle management.
Collaborate with software engineers, data scientists, manufacturing experts, and cloud architects to deliver enterprise AI solutions.
Ensure AI applications meet production requirements for scalability, reliability, security, and maintainability.
Required Skills
Programming & AI
Strong expertise in Python.
Hands-on experience with PyTorch and/or TensorFlow.
Extensive experience with supervised, unsupervised, and reinforcement learning techniques.
Strong understanding of deep learning architectures and model optimization.
Generative AI
Experience building production-grade Generative AI applications.
Strong knowledge of:
Large Language Models (LLMs)
GPT
BERT
Transformers
Diffusion Models
Fine-tuning and Prompt Engineering
RAG architectures
Agentic AI
Hands-on experience with:
LangChain
AutoGen
CrewAI (preferred)
Multi-Agent Systems
AI Orchestration Frameworks
AWS AI & Cloud
Hands-on experience with:
Amazon Bedrock
AWS SageMaker
AWS AI/ML Services
AWS Lambda
API Gateway
S3
ECS/EKS (preferred)
MLOps
MLflow
Docker
CI/CD Pipelines
Model Deployment
Model Monitoring
Version Control
Pipeline Automation
Manufacturing AI (Preferred)
Predictive Maintenance
Anomaly Detection
Quality Inspection
Manufacturing Analytics
Production Optimization
Digital Twins
Industrial IoT
Sensor Data Analytics
Performance Engineering
Model Quantization
Model Pruning
Tensor Optimization
GPU Optimization
Performance Benchmarking
Inference Optimization
Preferred Qualifications
Experience with NVIDIA Omniverse or Digital Twin platforms.
Exposure to Industrial IoT (IIoT) and manufacturing systems.
Knowledge of computer vision for industrial applications.
Experience deploying AI applications in cloud-native environments.
Familiarity with Kubernetes and containerized AI workloads.
Strong understanding of software engineering best practices and scalable system design.
Education
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related quantitative discipline with 7–10 years of professional experience.
Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field with 5–6 years of relevant industry experience.
Why Join Applix?
Work on cutting-edge AI and Generative AI technologies.
Build enterprise-scale AI products for global manufacturing leaders.
Opportunity to work with Digital Twins, NVIDIA Omniverse, AWS AI/ML, and Agentic AI.
Collaborative engineering culture with opportunities to innovate and influence product direction.
Competitive compensation, learning opportunities, and career growth in a rapidly evolving AI landscape.
Ideal Candidate Profile
The ideal candidate is a hands-on AI engineer with strong software engineering fundamentals who has successfully built and deployed production-grade AI/GenAI applications. Experience with LLMs, Agentic AI frameworks, AWS AI services, MLOps, and scalable cloud-native architectures is essential. Exposure to manufacturing, industrial AI, or digital twin technologies will be a significant advantage.

Work arrangement
No