Data Scientist Consultant with Gen AI

Position: Data Scientist Consultant with Gen AI
Location: Remote Duration: 6-12 Months+

As the data Science consultant, you should have the common traits and capabilities that are listed Essential Requirements and meet many of the capabilities listed in Desirable Requirements

Essential Requirements and Skills

• 10+ years working with customers in the Data Science and Data Analytics field.
• 5+ years developing AI Solutions for large customers.
• 2+ years working in AI Solutions that leverage Neural Network based solutions, especially within the context of NLP.
• Extensive knowledge of statistical analysis, modelling, transformer architectures and word embeddings.
• Very strong knowledge of LLMs, prompt engineering, guardrails, model chaining, fine tuning, and training. Experience with supervised and unsupervised training, PEFT, LoRA and RLHF.
• Detailed knowledge of latest developments in LLM related techniques such as external data integration using RAG, Reinforcement learning, Transfer Learning and Data Annotation. Detailed knowledge and experience with Agentic workflow solutions.
• Experience with RAG related tools such as Nvidia RAG LLM Playground, Nvidia Query Router, Nvidia Guardrails and Nvidia AI Workbench, Self-reflection techniques and NeMo Guardrails. Experience with GraphRAG
• Hybrid search using Milvus.
• Knowledge and ability to deploy and use the NIM Operator, its related tooling and the Nvidia Blueprints, including Multimodal PDF Data Extraction blueprint.
• Ability to integrate PowerScale RAG Connector with ingestion pipeline.
• Detailed knowledge of embeddings and embeddings models. Ability to evaluate embeddings engines and perform pre- and post-retrieval optimization.
• Ability to leverage NoSQL (such as Redis) and Vector Databases. Good SQL knowledge is required.
• Experience with working with Vector Databases such as PGVector and Milvus.
• Extensive experience and knowledge with using Python, PyTorch, TensorFlow, TensorRT, and Jupyter notebooks.
• Good knowledge of Gradio.
• Knowledge of CUDA libraries, Langchain modules, LlamaIndex, Pandas and other related libraries. Knowledge of Langgraph and Lansgsmith
• Knowledge of Mistral LLM and Gemma LLM Architectures.
• Hands on knowledge of the Nvidia AI tool suite such as NeMo Framework, Triton Inference Server, Nvidia NIMs, Nemo Retrieved Embeddings Microserver (NREM), Nvidia ChainServer and others.
• Hands on knowledge and experience of working on AMD GPUs and the associated AMD AI tool suites such as ROCM, OpenMP, OpenCL, HiPify and MIOpen.
• Good working knowledge of Hugging Face Portal and Interfaces, including usage of Hugging Face Models.
• Experience with utilizing LLMs to support the application development lifecycle (SDLC), such as using it for code completion, test analysis and code summarization. Experience with defining an ROI strategy when introducing AI in the SDLC.
• Experience with implementing and fine-tuning AI models for code assistants, including integration with development environments such as Visual Studio Code.
• Experience with utilizing AI models to support the software development lifecycle (SDLC), including code completion, test analysis, and code summarization.
• Familiarity with Linux.
• Experience using popular MLOps/LLMOps and AIOps tools such as SLURM, Cvrg.io, Kubeflow, mlflow, Kserve, vLLM and Torchrun.
• Experience with using techniques to optimize large models.
• Ability to evaluate models using well known metrics such as BLEU and Rouge. Ability to consult customers on the best models aligned to specific customer use cases using validation metrics, probability distributions, statistical inference and hypotheses testing. Ability to define and implement performance metrics to evaluate scalability of AI solutions. Familiarity with the GenAIPerf tool.
• Ability to integrate tuned model with Visual Studio (VS) Code integrated development environment (IDE).
• Ability to built test frameworks for AI models.
• Ability to consume API endpoints for data querying and ingestion
• Ability to influence and interact with confidence and credibility at all levels within the Dell Technologies companies and with our customers, partners, and vendors.
• Experience working on project teams within a defined methodology while adhering to margin, planning and SOW requirements.
• Ability to be onsite during customer workshops and enablement sessions.

Desirable Requirements and Skills

• General awareness of Dell Technologies products. Good understanding of GenAI related Dell Validated Designs (DVDs) and Dell white papers (DRDs).
• Knowledge of deploying the Nvidia Digital Human blueprint, based on ACE, A2F and Nvidia RAG. Knowledge of the Nvidia Tokkio pipelines
• Knowledge and experience of video processing AI techniques and their tooling such as CA-RAG, VLM and Nvidia VSS Blueprint
• Knowledge and understanding of IBM Watson ecosystem.
• General knowledge of TensorBoard, Hugging Face AutoTrain and Hugging Face Text Generation Inference.
• Operational Knowledge of Vendor supported Kubernetes distributions such as OpenShift, Tanzu and Rancher.
• In possession of the Certified Kubernetes Developer (CKD) certification is a plus.
• University Degree aligned to Machine Learning or Data Science is a plus.