Data Scientist

Senior Technical Recruiter at Brooksource

Data Scientist

Location: Houston

Contract Type: 6-Month Ongoing Contract (potential to hire Fulltime)

• Design & deliver GenAI solutions: Architect and implement LLM/LVM applications (text and, where applicable, vision) including prompt strategies, guardrails, evaluation metrics, cost/latency optimization, and production rollout.
• Build robust RAG systems: Stand up end‑to‑end RAG pipelines (ingestion → chunking → embedding → retrieval → synthesis), with observability, feedback loops, and AB testing for groundedness and hallucination control.
• Fine‑tune foundation models: Select, adapt, and fine‑tune open and hosted models for domain‑specific tasks using efficient techniques (LoRA/QLoRA, PEFT, parameter‑efficient adapters), and manage evaluation datasets.
• Develop agentic workflows: Implement multi‑step, tool‑using agents for real‑time, context‑aware operations; orchestrate planning, memory, and tool calling with safe‑execution policies.
• ML/LLM engineering: Build high‑quality Python code, reusable libraries, and APIs; implement CI/CD, testing, experiment tracking, and model/version governance.
• Data & platforms: Partner with data engineering to operationalize pipelines on enterprise platforms (e.g., Databricks/Snowflake) and integrate with cloud AI/ML services.

• Statistics
  , Multivariate Calculus
  , Linear Algebra
  , Optimization (you can explain choices and trade‑offs in model behavior based on these principles).

• Advanced Python (clean architecture, typing, packaging, testing; performance profiling and async where appropriate).
• Deep Learning:
  
  Tensor Flow or Py Torch

• Large Language/Vision Models (LLM/LVM): Hands‑on with multiple providers/models (e.g.,
  Gemini
  , GPT
  , Claude
  , Llama
  ) and their APIs.
• Model fine‑tuning: Proven experience fine‑tuning foundation models for domain tasks; evaluation design and data curation included.
• Retrieval‑Augmented Generation (RAG): Ability to design and implement robust RAG systems for real‑time, context‑aware applications.
• Prompt engineering & agentic workflows: Advanced prompt design (system/task/reflection patterns) and building multi‑step AI agents
  .
• Vector databases/search & embeddings: Practical experience with vector indexing, similarity search, and embedding selection/management.

• Version Control: Git (Git Hub/Git Lab/Bitbucket)
• Databases:
  
  SQL and No
  
  SQL (e.g.,
  MongoDB
  , Cassandra
  )
• Cloud: Hands‑on with one or more of AWS
  , Azure
  , GCP
  , specifically AI/ML & data services (e.g.,
  AWS Sage Maker
  , Azure Machine Learning
  , Google Vertex AI
  )

• Vector stores/search: FAISS, Milvus, Weaviate, Pinecone; hybrid (BM25 + vector) retrieval; reranking.
• LLMOps/observability: MLflow, Lang Smith, Open Telemetry, Prometheus, dashboards for cost/latency/quality; offline & online eval (e.g., RAGAS/Deep Eval style).
• Orchestration & data: Airflow/Prefect;
  Kafka/Event Hubs;
  Delta/Parquet;
  Unity Catalog/governance.
• MLOps patterns: Canary/shadow deployments, feature flags, AB testing, blue‑green rollouts.
• Domain experience: Background in complex, datarich industries (e.g., energy, manufacturing, industrial IoT) is a plus.

• Vision insurance
• Medical insurance

Referrals increase your chances of interviewing at Brooksource by 2x

Eight Eleven Group provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.