AI/ML Engineer

Company Description

Global Technology Partners is a premier partner for digital transformation, with a diverse team of software engineering experts in the US and India. They combine strategic thinking, innovative design, and robust engineering to deliver exceptional results for their clients.

GTP Labs is our internal R&D and client-facing innovation group. You’ll prototype, evaluate, and productionize AI features across our products—then help customers adopt them. We’re looking for a strong junior who can grow into leading our AI/ML team.

Experience:

Responsibilities

Build & Experiment

• Design rapid POCs for LLM-powered features (RAG, agents, tool use) and graduate the best ideas into roadmap items.
• Stand up MCP servers over OpenAPI specs to enable “ask & test the API” experiences.
• Create evaluation harnesses (offline & human-in-the-loop) for prompts, models, and pipelines.

Productize

• Ship ML/LLM services (APIs, microservices) with clean interfaces, telemetry, tests, and CI/CD.
• Implement guardrails (PII handling, redaction, safety filters) and quality gates.

Data & MLOps

• Build datasets (label/curate), retrieval indexes, vector stores, and monitoring dashboards.
• Own experiment tracking and model/artifact versioning; help with cost/performance tuning.

Partner with stakeholders

• Work closely with Product, Backend (Java/Spring), Frontend (Angular), and Customer teams; write clear docs and present findings

Ideal candidate(s) must have

• Solid Python (data/ML) and at least one of PyTorch or TensorFlow.
• Working knowledge of LLMs: tokenization, embeddings, RAG, basic fine-tuning/LoRA, prompt design, evaluation.
• API engineering: build/consume REST; JSON; pagination; auth; rate limits.
• Retrieval & storage: one vector DB (pgvector, Pinecone, Weaviate, or similar) + SQL basics.
• Packaging & delivery: Docker, Git, testing, simple CI.
• Excellent written & spoken communication; strong product sense; ownership mindset

Nice to have

• LangChain/LlamaIndex; agents (CrewAI/AutoGen); MCP (Model Context Protocol).
• Cloud: AWS/Azure/GCP (S3, Lambda, Bedrock/Azure OpenAI, basic IAM).
• Document AI (OCR, layout/structure), OpenAPI tooling, Postman/Newman, Spectral, Dredd/Schemathesis.
• Frontend familiarity (Angular/TypeScript) or Java/Spring Boot integration experience.
• Experiment tracking (Weights & Biases/MLflow); Kubernetes; basic Kafka/stream processing

How we work

• Velocity + Rigor:

  short POC cycles with measurable evals; promote what wins.

• Security by design:

  PII handling, encryption, role-based access, audit trails.

• Mentorship:

  direct access to senior architects and product leaders; learning budget & GPU time.

Growth path

• 0–6 months:

  lead POCs end-to-end; own an evaluation framework; ship 1–2 features into production.

• 6–12 months:

  tech lead for a product work-stream

• 12–18 months:

  mentor juniors; co-own roadmap; drive customer pilots—path to

  AI/ML Lead

Qualifications

• Bachelor’s or Master’s degree in Computers, or a related field with 1-4 years of relevant experience