Senior Data Science Engineer – LLMs
4 days ago
Company Description
Ray Business Technologies, an ISO CMMI Level 3 and ISO 27001:2022 certified company, brings over 16 years of IT service excellence to the global stage. With operations in the USA, Canada, Australia, Philippines, and India, we offer tailored solutions across diverse industries. Our talented team excels in using AI, Boomi, Cloud, ERP, CRM, CMS, BI, and custom software development to drive business growth and innovation. We pride ourselves on our commitment to quality and a proven track record of successful projects.
Key Responsibilities:
- Design, build, and deploy LLM-based solutions (e.g., GPT, LLaMA, Claude, Mistral, etc.) for enterprise and consumer-facing applications.
- Fine-tune open-source or proprietary LLMs for domain-specific tasks using techniques like LoRA, PEFT, or prompt engineering.
- Develop and optimize pipelines for data preprocessing, model training, and inference.
- Collaborate with MLOps and engineering teams to productionize generative AI models at scale.
- Evaluate and experiment with retrieval-augmented generation (RAG), agent frameworks, and prompt orchestration.
- Research and stay updated on the latest in generative AI, including multi-modal models, diffusion models, embeddings, and vector search.
- Work with cross-functional teams to gather requirements, build prototypes, and deliver high-impact AI solutions.
- Ensure model safety, fairness, and interpretability, and implement guardrails to mitigate hallucinations and biases.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
- 5+ years of experience in data science or machine learning engineering.
- Strong hands-on experience with LLMs (e.g., OpenAI, Cohere, Meta, Hugging Face Transformers).
- Experience with model fine-tuning, prompt engineering, and evaluation techniques.
- Proficiency in Python and ML libraries such as PyTorch, TensorFlow, Hugging Face, LangChain, or similar.
- Experience with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG systems.
- Knowledge of MLOps and deployment tools (e.g., Docker, Kubernetes, MLflow, Ray).
- Solid understanding of NLP, deep learning, and generative modeling techniques.
Preferred Qualifications:
- Experience with multi-modal AI (e.g., image + text models).
- Prior work in deploying AI agents or building applications using frameworks like LangChain, LlamaIndex, or Semantic Kernel.
- Contributions to open-source LLM or GenAI projects.
- Experience in privacy-preserving ML and ethical AI practices.
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