Full Stack AI Engineer

VySystems

United States

Remote

USD 140.000 - 210.000

Vollzeit

vor 19 Stunden
Sei unter den ersten Bewerbenden

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Zusammenfassung

VySystems is hiring a senior Developer for AI Development & Engineering to design, build, and operate production AI systems end to end. You will work across the full AI stack, from ML to LLM-powered applications, with a focus on observability, safety, and scalable deployment on Azure.

You will collaborate with product and security teams, implement MLOps practices, and mentor engineers, ensuring high-quality solutions in a fully remote, globally distributed team.

Qualifikationen

  • Bachelor's or Master's degree in CS/ML/Data Science or equivalent practical experience.
  • 4+ years of professional software engineering, with at least 2 years shipping ML/AI systems in production.
  • Strong Python and ML libraries (PyTorch/TensorFlow, scikit-learn, pandas, NumPy).
  • Experience deploying LLM-based applications with major model providers (Anthropic Claude, Azure OpenAI, OpenAI).
  • Hands-on RAG and embeddings with at least one production vector store.
  • Proficiency with AI coding tools like Claude Code and Cursor, plus strong manual coding skills.
  • Git, branching strategies, and PR-based reviews.
  • CI/CD pipelines (Azure DevOps, GitHub Actions) for production workloads.
  • Azure deployment (AKS, App Service, Functions, Azure AI/ML) and Docker.
  • Strong written and verbal communication; able to explain modeling decisions to non-technical stakeholders.
  • Proven ability to thrive in a fully remote, globally distributed team.

Aufgaben

  • Design, train, evaluate, and ship ML/DL models for business problems.
  • Build LLM-powered applications using Claude/OpenAI/Azure OpenAI.
  • Develop RAG systems with embeddings and vector stores.
  • Create agentic workflows with guardrails and evaluation.
  • Apply prompt engineering and fine-tuning; evaluate with offline/online metrics.
  • Build data pipelines on Azure ensuring quality and lineage.
  • Deploy and operate AI services with MLOps: retraining, drift detection, rollback.
  • Use AI coding assistants effectively alongside manual coding.
  • Manage source code in Git with clean branching and PR reviews.
  • Build and maintain CI/CD pipelines for AI services.
  • Deploy services on Azure (AKS, App Service) and with Docker.
  • Communicate modeling decisions to stakeholders; collaborate with product/security.
  • Mentor engineers on AI-assisted development and LLM patterns.
  • Conduct design/code reviews with emphasis on safety and observability.

Kenntnisse

Python programming
ML model development
Git & code review
CI/CD pipelines
Communication

Ausbildung

Bachelor's or Master's in CS/ML/Data Science

Tools

PyTorch
TensorFlow
Scikit-learn
Pandas
NumPy
Claude Code
Cursor
Azure DevOps
GitHub Actions
Docker
AKS
Terraform
Bicep
OpenAI/Claude/Azure OpenAI

Jobbeschreibung

We are hiring a senior Developer for AI Development & Engineering to design, build, and operate production AI systems end to end. You will work across the full AI stack: classical machine learning, deep learning, and modern generative AI (LLMs, RAG, and agentic workflows). You will turn ambiguous business problems into AI capabilities our users trust, taking ownership from data through deployment, monitoring, and iteration.

Our developers work fluidly across AI-assisted coding (Claude Code, Cursor), AI ML /Clude and traditional manual coding, deploying onto Azure with Git-based workflows and CI/CD. We expect strong software engineering instincts, comfort with experimentation, and a bias toward making AI systems observable, evaluable, and safe in production.

Key Responsibilities
  • Design, train, evaluate, and ship machine learning and deep learning models (classification, regression, ranking, vision, NLP, time series) against well-defined business and scientific problems.
  • Design and implement LLM-powered applications using major model providers (Claude/Anthropic, Azure OpenAI, OpenAI, or equivalents).
  • Build retrieval-augmented generation (RAG) systems, including chunking strategies, embeddings, vector store selection (e.g., Azure AI Search, pgvector), and re-ranking.
  • Develop agentic workflows with tool use and orchestration; implement guardrails, evaluation harnesses, and human-in-the-loop review where appropriate.
  • Apply prompt engineering, fine-tuning, and structured output techniques; measure quality with offline evals and online metrics.
  • Build and maintain robust data and feature pipelines on Azure; ensure data quality, lineage, and reproducibility.
  • Productionize models with sound MLOps practices: versioning, automated retraining, drift detection, and rollback strategies.
  • Use AI coding assistants (Claude Code, Cursor) effectively alongside traditional manual coding — choosing the right approach for each task and reviewing AI-generated code with rigor.
  • Manage source code in Git using a clean branching strategy and pull-request-based review.
  • Build and maintain CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for automated testing, packaging, and deployment of AI services.
  • Deploy and operate services on Azure using containers (Docker), orchestration (Kubernetes/AKS), and infrastructure-as-code (Terraform or Bicep).
  • Instrument AI systems with logging, tracing, and evaluation pipelines so that quality, latency, and cost can be observed and managed over time.
  • Partner with security and compliance to address data privacy, PHI/PII handling, prompt injection, and model risk in regulated contexts.
  • Work directly with product, scientific, and business stakeholders to scope problems, set realistic expectations, and choose the right level of AI sophistication for the job.
  • Mentor engineers on AI-assisted development practices and on the patterns and pitfalls of LLM-based systems.
  • Conduct rigorous design and code reviews; advocate for evaluation, safety, and observability as first-class concerns.
Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Mathematics, Statistics, or a related field — or equivalent practical experience.
  • 4 + years of professional software engineering experience, with at least 2 years building and shipping ML or AI systems in production.
  • Strong proficiency in Python and core ML libraries (PyTorch and/or TensorFlow, scikit-learn, pandas, NumPy).
  • Hands-on experience deploying LLM-based applications using major model providers (Anthropic Claude, Azure OpenAI, OpenAI, or open-source models).
  • Practical RAG and embeddings experience, including at least one production vector store.
  • Demonstrated proficiency with AI coding tools such as Claude Code and Cursor, balanced with strong manual coding fundamentals.
  • Solid command of Git, branching strategies, and pull-request-based code review.
  • Hands-on experience building and operating CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for production workloads.
  • Hands-on experience deploying services on Azure (AKS, App Service, Functions, Azure AI/ML services, or similar) and with containerization (Docker).
  • Strong written and verbal communication; able to explain modeling decisions and trade-offs to non-technical stakeholders.
  • Proven ability to thrive in a fully remote, globally distributed team.
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