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Bolsa de trabajo tester sr Híbrido - OCC

19 resultados

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Senior Data Scientist

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SAP HCM SR.

$65,000 - $70,000 Mensual

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Job Description: Senior Salesforce Developer A multinational consumer goods company is seeking a Senior Salesforce Developer to join its regional Digital IT team. The ideal candidate will have a ...

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SR DBA MS SQL

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Sr. .Software Engineer (.Net & Angular)

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At our company, all individuals participating in the recruitment process will be considered without distinction. We are committed to fostering a diverse and inclusive work environment, promoting equal ...

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Consultor SAP SD

$80,000 - $90,000 Mensual

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Bolsa de trabajo Ernst & Young

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Ingeniero de diseño sr

$55,000 - $65,000 Mensual

Actividades Diseñar y desarrollar nuevos productos conforme a requerimientos del cliente. Generar y mantener estructuras de producto (BOM's), hojas de ruta y planos. Coordinar validaciones, prueb ...

Aceros Beck S.A de C.V
Coah.
  • 1

Hace 2 días

Senior Data Scientist

$60,000 - $70,000 Mensual

FINASTRA en

Sobre el empleo

Categoría: Tecnologías de la Información - Sistemas
Subcategoría: Big data
Educación mínima requerida: Universitario titulado

Detalles

Contratación:

Permanente

Horario:

Tiempo completo

Espacio de trabajo:

Híbrido

Descripción

Job Description


What will you contribute?

We are seeking an experienced Senior Data Scientist to join our AI innovation team, with a specialty in developing and deploying production-grade Large Language Model (LLM) systems. The ideal candidate will be at the forefront of artificial intelligence technology, with deep experience across the full lifecycle of LLM applications - from research and development to production deployment and monitoring.


In this role, you will collaborate with cross-functional teams to design, implement, and optimize LLM-based solutions that drive business value across our internal functions and client-facing products. You will be responsible for building robust, scalable AI systems that can perform a wide variety of natural language tasks while maintaining high standards of reliability, efficiency, and ethical AI practices.


Key responsibilities & deliverables:

  • Design, develop, and deploy production-grade large language model systems across a wide variety of applications (e.g. RAG, text-to-SQL, specialized agents etc., summarization, etc.)
  • Architect and implement agent and multi-agent systems leveraging state-of-the-art LLM frameworks
  • Creation of tools and functions to enhance LLM capability
  • Establish and maintain model lifecycle management practices, including version control, evaluation metrics, and performance monitoring
  • Optimize LLM applications for production environments, balancing performance, cost, and latency requirements
  • Perform robust model validation and security assessments of LLM systems
  • Collaborate closely with product teams, data engineers, and software engineers to integrate LLM capabilities into products and services
  • Lead technical discussions and present complex AI concepts to both technical and non-technical stakeholders
  • Stay current with the rapidly evolving LLM landscape and implement best practices
  • Mentor junior data scientists and engineers across the organization in LLM development techniques


Required skills & experience:

  • 5+ years of professional experience in data science or machine learning engineering
  • Proven experience developing and deploying production-grade large language model systems
  • Strong proficiency in Python and related data science/ML libraries
  • Experience with LLM frameworks such as LangGraph or similar orchestration tools
  • Practical knowledge of prompt engineering, fine-tuning, retrieval-augmented generation, text-to-sql, and other related LLM tasks
  • Experience implementing agent and multi-agent systems with LLMs
  • Strong knowledge of deploying LLM systems and agents in production environments
  • Strong understanding of model lifecycle management and monitoring practices
  • Familiarity with cloud environments (e.g. Azure, databricks) and MLOps best practices
  • Experience with distributed computing and handling large-scale data processing
  • Thorough understanding of security best practices around LLM systems
  • Excellent collaboration skills and experience working with cross-functional teams
  • Strong knowledge of software development best practices (version control, CI/CD, testing)
  • Exceptional leadership, communication, and presentation skills
  • Advanced degree (MS or PhD) in Computer Science, Machine Learning, or related technical field


Technical Skills:

Aside from Python and SQL, we do not require previous working experience with most of the other skills listed below.

  • Programming Languages: Python (required), SQL
  • ML/LLM Frameworks: LangChain, LangGraph, Hugging Face Transformers, PyTorch, TensorFlow, or equivalent
  • Vector Databases: Pinecone, Weaviate, Milvus, Qdrant, or similar
  • Cloud Platforms: Azure, Databricks, AWS, or equivalent
  • MLOps Tools: MLflow, Weights & Biases, Kubeflow, or similar
  • Development Tools: Git, GitHub/GitLab, CI/CD pipelines
  • Data Processing: Pandas, PySpark, Dask, Spark, or equivalent
  • Containerization: Docker, Kubernetes
  • API Development: FastAPI, Flask, Langgraph Platform
  • Monitoring & Observability: Langsmith, Prometheus, Grafana, or similar



Benefits:

  • Major medical Insurance
  • Life Insurance
  • Food vouchers
  • Savings fund (after your first year at Finastra)
  • Retirement plan (after your first year at Finastra)
  • Annual Bonus
  • Christmas bonus of 25 days
  • 23 vacation days
  • Unlimited PTO



Recuerda que ningún reclutador puede pedirte dinero a cambio de una entrevista o un puesto. Asimismo, evita realizar pagos o compartir información financiera con las empresas.

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