Why Redian, and why this shape of team
You've landed here because you need AI/ML developers for a team based in or serving Boston, USA, and you're weighing whether to hire locally, use a marketplace, or engage a delivery partner. This page explains how Redian Software delivers exactly that engagement — onsite, AI/ML developers, aligned to Boston business hours (EST / EDT), on a commercial model that scales from a single engineer to a full offshore cell.
AI/ML Developers — what our engineers actually do
Redian's AI/ML practice ships production LLM systems, not demos — RAG over your document corpus with citations and permissioning, agentic workflows that call your existing APIs safely, fine-tuned classification and extraction models where LLMs are too slow or expensive, and the LLMops plumbing (eval harnesses, prompt versioning, cost telemetry, guardrails) that keeps a GenAI feature safe for a real customer. We work across Anthropic (Claude), OpenAI (GPT), open-weight models (Llama, Mistral), and the vector-store / orchestration layer.
Seniority mix: ML engineers (3–5 yrs, model fine-tuning, RAG, evaluation), senior ML engineers (5–8 yrs, model architecture, LLMops, cost/latency), and applied-AI leads (8+ yrs, product-AI conversations).
The Boston context
Boston's tech scene is anchored by biotech, healthcare, edtech, fintech and the MIT / Harvard research spillover — it's a market where deep domain expertise (regulatory, clinical, financial-services compliance) matters more than pure engineering velocity. The hiring floor for senior ICs is high, the cycle is 10+ weeks for a niche skill, and the local supply for JVM / Java at scale, data / ML engineers, and healthcare-domain product engineers is chronically undersupplied.
Redian ships EST-aligned coverage from India — engineers online for your entire Boston morning, from standup through mid-afternoon. Standups, code review, incident response and design conversations happen inside that overlap; work after is asynchronous with a written handover you pick up the next morning.
Onsite engagement — the mechanics
Onsite engagement — engineers work from your office. For clients whose delivery model needs on-the-ground presence — regulator-mandated controls, hardware access, in-room collaboration with an internal team, or leadership preference — Redian deploys engineers to your location on a per-diem or medium-term contract. We handle visa, work-permit, accommodation and travel logistics from our side; you provide the desk, badging, and access to the systems the engineer will touch.
How the commercials work. Onsite carries a different rate card than remote — day-rate is higher to cover the engineer's living cost and per-diem, and minimum engagement is usually 3 months to make the mobilisation worthwhile. We can also blend the models: a small onsite core (2–3 engineers) plus a larger remote build team, so you get the trust of physical presence without the cost of an all-onsite ramp.
Commercials and how to start
Rates depend on the exact seniority mix and length of engagement, but as a rule: a onsite AI/ML developer from Redian lands well below the loaded cost of the equivalent local hire in Boston, without dropping seniority. Minimum engagement is one month for remote, three months for onsite. Rate card, sample CVs of currently-available engineers, and reference clients in your industry — happy to send those on the first call, subject to NDA.
How the first two weeks look: we scope the roles, seniority mix and start date on a 30-minute discovery call. We share 3–5 CVs matched to the brief within 3 business days. You interview shortlist candidates directly. The chosen engineer(s) start inside 1–2 weeks (4–10 weeks if onsite mobilisation is needed), on your tools, in your workflow, with named Redian consultant oversight.
No lock-in, no minimum quarter. If an engineer isn't a fit inside the first two weeks, we swap them, no charge. If you need to scale up or down mid-engagement, we do it — that flexibility is the whole point of engaging a partner instead of hiring FTEs.