AI Engineer
ABOUT BEEWEB
BeeWeb is a software development company with 10 years of industry expertise. We offer a range of outsourcing software development services, spiced up with AI, top-tier technologies, and agile approaches. Our primary goal is to help businesses succeed through technology with a human touch. So, humans make the greatest asset at BeeWeb. They are given exciting new opportunities to master their career journeys, go further, reach higher, and realize their true potential.
ABOUT THE ROLE
We are looking for an AI Systems Engineer with expertise in AI models, LLMs, vision models, deep learning, and cloud infrastructure. The role involves designing, deploying, and optimizing scalable AI applications that leverage LLMs, Vision AI, and Retrieval-Augmented Generation (RAG) for enhanced decision-making and automation. The ideal candidate will have experience in AI model development, fine-tuning, deployment, and integration into MLOps and data pipeline ecosystems, as well as optimizing inference pipelines and building RAG systems using vector databases.
🏆 ABOUT YOU
Missions
1. AI & Machine Learning Model Development:
Develop, fine-tune, and deploy LLMs (e.g., ChatGPT, Claude, Llama, Phi) for intelligent decisionmaking applications.
Implement and optimize vision models (e.g., GPT-4o Vision, SAM, YOLO) for computer vision tasks.
Work with audio models (e.g., Whisper, Vall-E) to support speech recognition and voice-based AI applications.
Leverage text embeddings (e.g., Text Embedding 3 Large), image embeddings (e.g., CLIP, DINO), and audio embeddings (e.g., Wav2Vec, Whisper) to enhance model performance.
2. AI Pipeline Engineering & Deployment:
Design and implement scalable AI pipelines using Python (FastAPI, asynchronous architectures).
Utilize ML Flow for model monitoring and maintaining model registries.
Optimize inference pipelines to enhance response times for AI-based decision-making.
3. Retrieval-Augmented Generation (RAG) & Knowledge Systems:
Implement RAG systems using vector databases (e.g., Milvus) for knowledge retrieval and AI reasoning.
Develop data indexing pipelines for structured retrieval from MongoDB, PostgreSQL, and MinIO storage.
Integrate structured and unstructured data sources into AI workflows to improve model outcomes.
4. Data Engineering & Processing:
Develop event-driven data ingestion pipelines from CMS applications and internal/external data sources.
Preprocess and clean structured and unstructured data for AI consumption.
Optimize NoSQL (e.g., MongoDB, CosmosDB) and SQL (e.g., PostgreSQL) databases for AI applications
Your Profile
- 3+ years’ experience in relevant field.
- Experience with Generative AI and LLM Fine-Tuning.
- Background in AI Research and Applied Deep Learning.
- Familiarity with Multi-Agent AI Systems.
- Strong analytical and problem-solving capabilities.
- Ability to work both independently and within a team setting.
- Experience working in Agile development environments.
- Passionate about AI-driven automation and the future of AI-first applications.
Technical Stack
- Programming: Python (FastAPI, PyTorch, TensorFlow), SQL, NoSQL.
- AI/ML Frameworks: PyTorch, TensorFlow, Hugging Face Transformers, LangChain.
- LLM Experience: OpenAI GPT, Claude, Llama, RAG implementations. (Preferred) Vision AI: YOLO, SAM, CLIP, DINO, OpenCV. (Preferred)
- Vector Databases: Milvus, FAISS, Weaviate. (Preferred)
- Cloud & DevOps: Docker, Kubernetes.
- MLOps: MLFlow, Prometheus, Grafana. (Preferred)
- API Development: RESTful, GraphQL, WebSocket integration.
WHAT CAN YOU EXPECT FROM OUR RECRUITMENT PROCESS?
Step 1: Intro Call
Step 2: Culture Fit Interview
Step 3: Client Interview
Step 4: Job offer
All relevant and interested candidates should submit their CVs to hr@beewebsystems.com email address
with the note of "AI Engineer" in subject line.