Senior Engineer, Data and AI

Emploi pas sur LinkedIn

🕒 il y a 7 jours

🦀 Maryland – Distant

🦀 Maryland – Remote

⏰ Temps Plein

🟠 Senior

🚰 Ingénieur Data

🦅 Parrain de Visa H1B

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Cisive

Site WebLinkedInTous les Emplois

1001 - 5000 employés

Fondée en 1977

💼 Conseil

⚖️ Juridique

📦 Logistique

Consulting • Legal • Logistics

Cisive est une entreprise spécialisée dans le dépistage des talents et la gestion des risques de la main-d'œuvre, axée sur la conformité. Elle propose des vérifications des antécédents, des tests de dépistage de drogues et de santé au travail, une surveillance continue, des services électroniques I-9 et du renseignement exécutif via une plateforme unique et intégrée. Cisive sert des industries fortement réglementées, en particulier la santé et le transport, offrant des produits spécialisés comme PreCheck pour la santé et Driver iQ pour le dépistage des conducteurs, avec un accent sur des résultats rapides, précis et conformes à la réglementation pour les employeurs.

Description

• This position has a wide range of responsibilities that includes both data and AI engineering. • They will be responsible for designing and implementing data infrastructure to extract, clean, move and store data. • They will need the ability to independently develop AI/ML systems and products for both internal and external use. • They will communicate with business stakeholders to understand their needs and develop solutions to address them.

🎯 Exigences

• Degree in Computer Science, Physics, Mathematics, or a similar field; Master's degree a plus. • 3–5 years of experience as a data engineer, ML engineer, AI engineer, AI infrastructure engineer, or in a similar role. • Strong Python skills for building, training, and deploying both traditional ML models and modern AI applications — including LLM-based systems, RAG pipelines, and agentic workflows. • Proficiency in feature extraction/transformation and model selection, training, and evaluation. • Experience with LangChain and LangGraph for building agentic/AI workflows, and working with LLM APIs such as the Claude and OpenAI SDKs. • Experience self-hosting and serving models with vLLM is a plus. • Proficiency building and serving APIs with FastAPI, using Pydantic for data validation and schema enforcement. • Solid grounding in statistical methods and experimental design (e.g., hypothesis testing, regression, causal inference) to validate models and ensure sound decision-making. • Experience deploying, monitoring, and maintaining models and AI systems in production, using tools such as MLflow (experiment tracking) and LangSmith/LangFuse (LLM tracing and evaluation). • Discover and characterize source data systems, understand and model the underlying business concepts, and build data models that organize data to meet operational and reporting needs. • Proficiency with databases (T-SQL, NoSQL) — writing and optimizing tables, queries, and indexes for scalability, reliability, and performance. • Design and implement pipelines to move and transform data between systems. • Experience with data warehousing concepts and platforms like Databricks; familiarity with Spark and Python for large-scale data processing. • Knowledge of cloud services, particularly Azure, for scalable data storage and processing. • Awareness of data quality, privacy, security, and compliance best practices.

🏖️ Avantages

• It's fun to work in a company where people truly BELIEVE in what they're doing! • We're committed to bringing passion and customer focus to the business.