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Ai Engineer Contract Jobs in Puerto Rico (NOW HIRING)

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Ai Engineer Contract information

What are AI engineer contracts?

AI Engineer contracts are agreements between companies and artificial intelligence engineers who work on a temporary or project basis to develop, implement, or maintain AI technologies. Contractors may be hired for specific projects like building machine learning models, automating processes, or integrating AI solutions into existing systems. Unlike full-time employees, contract AI engineers often work on a freelance or fixed-term basis, offering flexibility for both the employer and the engineer. These contracts typically outline the scope of work, duration, payment terms, and deliverables. Companies often use AI Engineer contracts to quickly access specialized skills without long-term commitments.

What are some common challenges AI engineers face when working on contract projects?

AI Engineers working on contract projects often encounter challenges like quickly adapting to new codebases and company processes, aligning with client expectations, and managing project scope within set timelines. Since contractors may have limited onboarding time, effective communication and time management are crucial for integrating with existing teams. Additionally, ensuring the transfer of knowledge and documentation at project completion is vital for long-term success and client satisfaction.

What are the key skills and qualifications needed to thrive as an AI engineer contract, and why are they important?

To thrive as an AI Engineer (Contract), you need strong expertise in programming languages (such as Python or Java), machine learning algorithms, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms, and version control systems is typically required, along with certifications in AI or machine learning being advantageous. Outstanding problem-solving skills, adaptability, and effective communication set top-performing contract AI engineers apart. These skills ensure efficient project delivery, seamless integration with teams, and the ability to develop innovative AI solutions that meet client needs.

What is the difference between Ai Engineer Contract vs Data Scientist Contract?

AspectAi Engineer ContractData Scientist Contract
Required CredentialsBachelor's or higher in CS, AI, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; experience with data analysis tools
Work EnvironmentTech companies, AI startups, R&D labsBusiness, finance, healthcare, and tech sectors
Employer & Industry UsagePrimarily in AI-focused roles across various industriesAcross industries for data analysis and insights

While both roles involve working with data and algorithms, Ai Engineer Contract focuses on developing AI models and systems, whereas Data Scientist Contract emphasizes analyzing data to derive insights. The roles often overlap but differ mainly in their core responsibilities and technical focus.

What are popular job titles related to Ai Engineer Contract jobs in Puerto Rico?

For Ai Engineer Contract jobs in Puerto Rico, the most frequently searched job titles are:

What job categories do people searching Ai Engineer Contract jobs in Puerto Rico look for?

The top searched job categories for Ai Engineer Contract jobs in Puerto Rico are:

What cities in Puerto Rico are hiring for Ai Engineer Contract jobs?

Cities in Puerto Rico with the most Ai Engineer Contract job openings:

Infographic showing various Ai Engineer Contract job openings in Puerto Rico as of August 2026, with employment types broken down into 74% Full Time, 20% Part Time, 2% Temporary, and 4% Contract. Highlights an 72% Physical, 4% Hybrid, and 24% Remote job distribution.

Senior AI Software Developer

Hewlett Packard Enterprise Development LP

Aguadilla, PR โ€ข Hybrid

$48.75 - $64.25/hr

Full-time

Re-posted 13 days ago


Job description

Senior AI Software DeveloperThis role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world.Our culture thrives onfinding new and better ways to accelerate what's next.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. If you are looking to stretch and grow your career our culture will embrace you.Open up opportunities with HPE.

Job Description:

The Senior AI Engineer owns end-to-end delivery of AI features-from design to production-while raising the engineering bar through code quality, reliability, and mentoring. The engineer will convert architecture into robust implementations, proactively manage risks, and ensure observable, secure, and performant AI systems. Important to have Good Networking knowledge

Responsibilities:
Solution Engineering & Delivery

  • Translate high-level designs into clear component contracts, APIs, and service boundaries.
  • Implement LLM integrations, RAG pipelines, agents, tool/function calling, and prompt strategies.
  • 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:

Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset

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.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

No Fees Notice & Recruitment Fraud Disclaimer

It has come to HPE's attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candidates. These scammers often seek to obtain personal information or money from candidates.

Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendorswill never charge any candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process.The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candidates and candidates shall be solely responsible to conduct such verification. Any candidate/individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that may result from any such communication.