Design, develop, and maintain scalable services and APIs for AI model inference, fine-tuning, and training-as-a-service.
Optimize backend systems for distributed computing environments, handling large-scale AI serving workloads.
Collaborate closely with application
developers to ensure smooth end-to-end integration.
Implement automated monitoring, logging, and alerting for AI services.
Ensure system security, performance, and scalability.
Troubleshoot and optimize system performance for high-traffic environments.
Research and experiment with emerging systems and AI technologies, bringing prototypes into production.
Requirements
Bachelor's degree in Computer Science,
Software Engineering, or a related field, plus:
5+ years of development experience, with at least 3 years in AI/ML-related projects.
Expert in Python (including asyncio, concurrency, multiprocessing).
Experienced in data preprocessing, feature engineering, and evaluation techniques.
Adept at working with databases (including non-relational and vector databases).
Proficiency in containerization and orchestration (Docker Compose, Kubernetes).
Familiarity with microservices architectures and message brokers (Kafka, RabbitMQ).
Capable of managing task queues and asynchronous processing (Celery or similar).
Skilled in monitoring & observability stacks (Prometheus, Grafana, ELK).
Committed to security best practices, performance optimization, and system scalability.
Well-versed in cloud platforms, including deploying distributed and edge AI systems.
Solid understanding of CI/CD, version control (Git), and agile workflows.
Enthusiastic about experimentation, rapid prototyping, and learning new technologies.
Role-Specific Expertise
A. Computer Vision
Preferred qualifications:
Solid foundation and strong fundamentals in Computer Vision.
Hands-on experience with inference toolchains (TensorRT, ONNX, Triton).
Proficiency with PyTorch or TensorFlow, including inference and training workflows.
Experience developing and optimizing deep learning pipelines for image/video tasks.
Familiarity with Stable Diffusion, GANs, Vision Transformers, and VLMs is a strong plus.
B. LLM / NLP
Preferred qualifications:
Strong understanding of Natural Language Processing and LLMs.
Familiar with LangChain, LlamaIndex, and vector databases (FAISS, Milvus, Qdrant).
Experience with inference engines (vLLM, Ollama, TGI, Text Generation Inference).
Familiar with LLM fine-tuning, serving, and optimization workflows.
Experience in embedding management, tokenization, and prompt optimization.
Understanding Retrieval-Augmented Generation (RAG) pipelines is a strong advantage.
Opportunity to work with cutting-edge AI systems in Computer Vision and LLM domains.
Supportive environment where your expertise directly shapes real-world products.
Diverse challenges in a professional, innovative, and fast-paced organization.
Access to top-tier hardware with GPU and dev tools for training and optimization.
A dynamic and creative work environment that encourages innovation and growth.
Competitive salary, regular performance reviews, and bonus opportunities.