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 — remote, 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.
Remote engagement — the mechanics
Remote engagement — this is our default delivery model. Engineers work from Redian's delivery centres in India, join your calls at your local hours, use your tools (Slack, Jira, Linear, GitHub, GitLab, Notion — whatever), and integrate with your existing workflow. You don't run their laptops, you don't manage their leave, you don't handle their tax — Redian does. Named engineers show up on your standups from day one.
Security controls that pass procurement. Managed Redian-issued devices with MDM, disk encryption and endpoint DLP; corporate VPN into your infra where you require it; IAM-integrated access (SSO, MFA, least-privilege); signed NDA and IP-assignment on every engineer; pen-test and SOC 2 evidence on request. The people you talk to are FTEs on Redian's payroll, not marketplace contractors.
Commercials and how to start
Rates depend on the exact seniority mix and length of engagement, but as a rule: a remote 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 (day-one remote), 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.