Own feature delivery for sprints/releases; maintain high code quality and documentation.
Modeling & Evaluation
Fine-tune models when needed; design evaluation harnesses and metrics.
Build A/B testing setups; track accuracy, latency, robustness, and task success rates.
Conduct error analysis; iterate using feedback efficacy loops and prompt refinement.
Data & Retrieval Engineering
Build ETL/ELT pipelines; curate datasets with metadata, lineage, and validation.
Implement vector indexing (chunking, embeddings, reranking), tune chunk size & overlap.
Enforce data governance: PII handling, redaction, consent, auditability.
MLOps & Platform Readiness
Containerize workloads (Docker); orchestrate deployments (Kubernetes/Helm).
Own CI/CD for ML: train → evaluate → package → deploy → monitor → rollback.
Maintain model/agent registries, experiment tracking, and reproducible environments.
Software Engineering & Integration
Build microservices and async inference paths; support batch/stream processing.
Integrate with enterprise auth, observability, telemetry, and logging.
Write unit/integration/e2e tests, performance benchmarks, and failure-injection tests.
Observability, Reliability & Performance
Instrument with metrics/logs/traces; define SLOs (latency, throughput, error rate).
Optimize inference: batching, caching (KV cache), quantization, token efficiency.
Implement guardrails (safety filters, jailbreak detection), auto-evals and alerts.
Security & Compliance
Apply secure coding practices; manage secrets, encryption, and least privilege.
Ensure compliance (data residency, consent, audit trails); respect IP policies.
Enforce policy-based access and content safety in user-facing features.
Collaboration & Mentoring
Review designs/PRs; coach L3 engineers on best practices.
Coordinate with AI Architects, Data Engineers, QA, and Product.
Education and Experience Required
Bachelor's or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline.
Typically, 7-10 years’ experience.
Knowledge and Skills
LLMs & Agents: Prompt engineering, function/tool calling, orchestration frameworks, RAG.
ML/DS: Evaluation metrics (precision/recall, BLEU/ROUGE where relevant), error analysis.
Data/RAG: Embeddings, similarity (cosine/IP), chunking, rerankers, vector DB operations.
Backend: Python (FastAPI/Flask), microservices patterns.
MLOps/Infra: Docker, Kubernetes, CI/CD, artifact management, GPU scheduling.
Observability: Metrics/logging/tracing, dashboards, automated evaluation pipelines.
Frameworks: PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex.
Data: Pandas, SQL/NoSQL, Parquet/Arrow, Kafka/queues.
Vector DBs: FAISS, Milvus, pgvector, Pinecone, Weaviate.
Ops: GitHub Actions/Azure DevOps, MLFlow/W&B
#LI-Hybrid
Additional Skills
Cross Domain Knowledge, Development Fundamentals, Développement complet, Ingénierie des données, Opérations d’apprentissage automatique, Réflexion conceptuelle, Rendement des TI, Science des données, Security-First Mindset, Technologies d'intelligence artificielle, Tests d'extensibilité
What We Can Offer You
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.
Let's Stay Connected
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
#puertorico
#networking
Job
- Engineering
- Job Level:
- TCP_04
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.
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