Role overview
*Data Scientist
Location**
: Houston
Contract Type
: 6-Month Ongoing Contract (potential to hire Fulltime)
Overview
- 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.
*Required qualifications
Mathematics & foundations**
- Statistics , Multivariate Calculus , Linear Algebra , Optimization (you can explain choices and trade‑offs in model behavior based on these principles).
What we're looking for
- Version Control: Git (GitHub/GitLab/Bitbucket)
- Databases:SQL and NoSQL (e.g., MongoDB , Cassandra )
- Cloud: Hands‑on with one or more of AWS , Azure , GCP , specifically AI/ML & data services (e.g., AWS SageMaker , Azure Machine Learning , Google Vertex AI )
- Enterprise data engineering platforms:Databricks , Snowflake
- *Azure AI Foundry:Hands‑on experience required
- Vector stores/search: FAISS, Milvus, Weaviate, Pinecone; hybrid (BM25 + vector) retrieval; reranking.
- LLMOps/observability: MLflow, LangSmith, OpenTelemetry, Prometheus, dashboards for cost/latency/quality; offline & online eval (e.g., RAGAS/DeepEval style).
- Orchestration & data: Airflow/Prefect; Kafka/Event Hubs; Delta/Parquet; Unity Catalog/governance.
- Containers & CI/CD: Docker, Kubernetes (AKS/EKS/GKE), GitHub Actions/Azure DevOps; infrastructure as code (Terraform).
- Safety & compliance: Content moderation, jailbreak resistance, prompt‑leakage mitigation, red‑teaming, privacy/PII handling.
- 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.
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.
Tags & focus areas
Used for matching and alerts on DevFound Contract Ai Machine Learning Deep Learning Data Science Mlops Generative Ai Pytorch Tensorflow Data Engineer