Associate AI/ML Developer

iSoftStoneWhite Plains, NY
Hybrid

About The Position

iSoftStone, Inc. is seeking an Associate AI Developer to help build and ship production-grade AI services. This training-based, early-career role is ideal for recent graduates eager to grow into hands-on AI engineers, working alongside senior developers on real client projects spanning agentic applications, orchestration, observability, and computer vision—across a cloud-agnostic stack.

Requirements

  • Recently graduated from, a degree/certificate program in Computer Science, AI/ML, Data Science, Engineering, or a related field.
  • Up to 2 years of practical experience (internships, co-ops, or substantial academic/personal projects) developing software or AI applications.
  • Hands-on exposure building AI services and integrations with one or more of: AWS (Bedrock, SageMaker), Azure (AI Foundry/AI Studio, Azure OpenAI), NVIDIA (CUDA, NIM, Triton), or open-source (LangChain, Pydantic, Python).
  • Solid Python foundation plus software engineering fundamentals (version control, testing, APIs, clean code).
  • Cloud-agnostic and portability-minded; strong problem-solver; open to learning and feedback in a fast-paced environment.

Nice To Haves

  • Familiarity with agentic patterns, tool-use orchestration, or the Model Context Protocol (MCP); RAG and vector search (Pinecone, Weaviate, FAISS).
  • Exposure to deep learning frameworks (PyTorch, TensorFlow), MLOps/observability (MLflow, OpenTelemetry), containers (Docker, Kubernetes), or CI/CD.
  • Prior internship, capstone, or project work involving AI, data, or cloud services

Responsibilities

  • Build AI services: Develop and help deploy services and microservices that integrate LLMs and classical ML (real-time APIs, batch, and event-driven workloads).
  • Agentic & orchestration: Contribute to agent workflows and tool-use orchestration using frameworks such as LangChain, with structured I/O via Pydantic.
  • Vision & deep learning: Help develop and integrate CNNs and vision models (classification, detection, OCR) into production pipelines.
  • Observability: Instrument services with logging, tracing, and evaluation hooks; help monitor quality, latency, cost, and drift.
  • Cloud-agnostic delivery: Build AI integrations on AWS, Azure, or NVIDIA tooling—and with open-source models—favoring portable, well-tested code.
  • Quality & collaboration: Write tests from specs, join code reviews and design discussions, and respond constructively to feedback.
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