Rc - Pricing Staff Ey Gds jobs at Ey in Mexico

To be updated

To be updated

Language Models (LLMs)Retrieval-Augmented Generation (RAG)Prompt EngineeringDevelopment of Generative AI applicationsProduction deployment of AI services (APIs, CI/CD, observability) Experience in fine-tuning (LoRA/PEFT) or specialization in contextual applications.

Bachelor's degree in fields such as Computer Science, Data Science, Statistics, Mathematics, or Engineering.
Strong foundation in software engineering.

Python, SQL, Git, and CI/CD

Azure AI (OpenAI, AI Foundry, AI Search)AWS BedrockGCP Vertex AIDatabricks

Semantic KernelLangChainLangGraphFastAPI or Flask

Azure AI SearchChromaDBVertex AIPineconeNeo4j

ChunkingIndexingRetrievalGrounding

PyTorch or TensorFlow

OpenTelemetryOpenLLMetryArize PhoenixLangfuseLangsmithRAGASDeepEval

DockerKubernetes

Develop and implement AI solutions using advanced techniques and methodologies.Collaborate with cross-functional teams to design and deploy scalable AI applications.Monitor and optimize the performance of AI models in production environments.Engage in continuous learning and application of emerging AI technologies.

To be updated

Position Requirements

Minimum Education Required:Bachelor's degree in computer science, Data Science, Statistics, Mathematics, or Engineering.

Advanced Python, advanced English, and strong knowledge of cloud technologies, dashboards, and Big Data.

Programming Languages and Databases:Python, R, SQL, NoSQL.

Tools and Platforms:Amazon SageMaker, GCP Vertex AI, Databricks, Kubernetes, MLflow, Docker, Flask, FastAPI

Data Visualization Tools:Tableau, Power BI.

Libraries and Frameworks:Scikit-learn, Keras, Pandas, NumPy, SciPy, TensorFlow, PyTorch.

Version Control and Deployment:Git, CI/CD.

Models and Techniques:Regression, Decision Trees, Clustering, Natural Language Processing (NLP), Neural Networks.

Big Data and ETL Technologies:Apache Spark, PySpark, Hadoop, Databricks, ETL

Develop and apply analytical models for data interpretation.Create data visualizations using tools such as Tableau and Power BI.Implement Machine Learning and Deep Learning techniques to solve problems.Collaborate with multidisciplinary teams to develop innovative solutions in Big Data

Key Responsibilities:

• Develop detailed project plans outlining scope, objectives, timelines, and resources required.
• Coordinate with team members to assign tasks and monitor progress towards project milestones.
• Identify and mitigate risks to ensure successful project delivery.
• Key deliverables that you will work on are comprehensive project plans, including Gantt charts, resource allocation schedules, status reports, meeting agendas, presentations to stakeholders and risk management strategies.
• Act as the primary point of contact for project stakeholders, providing regular updates on progress, issues, and changes.
• Facilitate effective communication between team members, management, and external partners as needed.
• Allocate resources effectively to ensure that project tasks are completed efficiently.
• Establish and enforce quality standards to ensure that deliverables meet or exceed customer expectations.
• Prepare regular progress reports for management and stakeholders, highlighting key achievements, risks, and issues.
• Identify lessons learned from each project and apply them to improve processes and methodologies.
• Stay updated on industry best practices and trends in project management to enhance overall project performance.

General Qualifications:

• Bachelor's degree in Business Administration, Project Management, Technology or related field.
• Minimum of 2 years of experience in project management or a related role.
• Proficiency in project management tools such as Microsoft Project, Asana, or Trello.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal abilities.
• Ability to work effectively in a fast-paced, dynamic environment.
• Certifications as CAPM, Scrum Master, PMP are a plus.

Specific Qualifications:

• Power Bi experience
• ERP implementation
• Program and portfolio management
• PMO setup and governance

To be updated