Strong Middle/Senior Data Scientist

On behalf of our Client from USA, Mobilunity is looking for a Senior Data Scientist

We are looking for a Senior Data Scientist with expertise in Large Language Models (LLMs) and
Generative AI to lead the design and delivery of end-to-end AI systems that generate
high-quality insights from complex unstructured datasets. This role requires strong ownership
across the full lifecycle from data preparation and model fine-tuning to RAG pipeline architecture
and scalable deployment on AWS.

Key Responsibilities:

• Architect and implement end-to-end LLM-based solutions for insight generation and
  automation
• Lead the design and optimization of Retrieval-Augmented Generation (RAG) pipelines,
  including ingestion, chunking strategies, embedding generation, indexing, and retrieval tuning
• Fine-tune, evaluate, and optimize LLMs using advanced techniques (e.g., instruction tuning,
  LoRA)
• Define and enforce best practices for data preprocessing, cleaning, normalization, and
  transformation across diverse data sources
• Provide hands-on guidance and code/data reviews for existing data scientists
• Help the team develop practical intuition for LLM fine-tuning and evaluation
• Establish simple, repeatable workflows for experimentation and iteration
• Prevent over-engineering and ensure focus on business outcomes
• Design scalable and cost-efficient AI/ML solutions leveraging AWS services
• Own the development of vector search infrastructure and embedding pipelines
• Establish robust evaluation frameworks for LLM outputs (accuracy, relevance, hallucination reduction)
• Collaborate cross-functionally with engineering, product, and business stakeholders to
  translate requirements into AI solutions
• Drive MLOps best practices including versioning, monitoring, CI/CD, and performance
  optimization
• Ensure data governance, security, and compliance in all AI workflows

Required Skills & Qualifications:

• Master’s or PhD in Computer Science, Data Science, Machine Learning, or related field (or equivalent experience)
• 5+ years of experience in data science, machine learning, or applied AI roles
• Experience mentoring or leading data scientists in applied ML/LLM projects
• Proven experience designing and deploying LLM-based solutions in production
• Hands-on experience fine-tuning open-source LLMs (Llama, Mistral, Qwen)
• Experience with LoRA / QLoRA approaches
• Ability to work with limited datasets and iterate quickly
• Strong understanding of trade-offs between model size, cost, and performance
• Strong expertise in RAG architectures and semantic search systems
• Deep understanding of NLP, embeddings, and transformer-based models
• Advanced proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow)
• Hands-on experience with vector databases (e.g., FAISS, Pinecone, OpenSearch, Weaviate)
• Strong experience with AWS ecosystem (e.g., S3, SageMaker, Bedrock, Lambda, EC2, Step
  Functions)
• Experience building scalable data pipelines and distributed systems
• Solid understanding of API design, microservices, and system integration

Mandatory skills:

real production experience with LLM
RAG pipelines (end-to-end)
fine-tuning (LoRA / QLoRA)
vector DB (FAISS / Pinecone / etc.)
AWS (S3, SageMaker, etc.)

Preferred Qualifications:

• Experience with RLHF, prompt optimization, and evaluation frameworks for LLMs
• Experience with real-time or streaming data pipelines
• Knowledge of cost optimization strategies for LLM workloads

English: B2