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 San Francisco Bay Area, 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 — AI/ML developers aligned to San Francisco business hours (PST / PDT), in either a remote or onsite model, on a commercial framework 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 to use. We work across Anthropic (Claude), OpenAI (GPT), open-weight models (Llama, Mistral).
Seniority mix: ML engineers (3–5 yrs), senior ML engineers (5–8 yrs, own model architecture, LLMops, cost/latency tradeoffs), and applied-AI leads (8+ yrs).
The San Francisco context
San Francisco and the Bay Area sit on top of the highest engineer salary floor in the world — a mid-level engineer clears USD 220K loaded, a senior clears USD 320K+, and a competitive hiring cycle for a senior IC still takes 12+ weeks. Whether you're an AI-native company in Hayes Valley, a fintech in South Park, or a healthtech vendor bound by HIPAA in Palo Alto, the calculus is the same — you need senior engineers, you cannot afford a full quarter to close each one.
In San Francisco specifically
In the Bay Area specifically, Redian's AI/ML engineers ship for AI-native Series B–D companies plus enterprise buyers running AI transformation programmes. Anthropic (Claude), OpenAI (GPT), open-weight models (Llama, Mistral) — the choice depends on cost, latency and data-residency.
Remote engagement — the mechanics
Remote engagement 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.
Time-zone overlap. We commit to a written working-hours overlap in the SOW — typically 4–6 hours of your San Francisco business day. Standups, code review, incident response and demos happen inside that overlap. Everything after is asynchronous with a written handover so you pick up the next morning.
Onsite engagement — the mechanics
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 San Francisco 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.
Commercials. 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.
Mobilisation timelines. 4–10 weeks depending on visa category (which we own end-to-end). If you need someone physically present sooner, we start remote from day one and switch to onsite as the visa lands — the same engineer, no handover.
Commercials and how to start
Rates depend on the exact seniority mix, engagement model (remote vs onsite) and length. As a rule: a remote AI/ML developer from Redian lands well below the loaded cost of the equivalent local hire in San Francisco, without dropping seniority. Onsite adds per-diem and mobilisation to the day-rate. Minimum engagement is one month for remote, three months for onsite. Rate card, sample CVs 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 roles, engagement model, 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. Chosen engineer(s) start inside 1–2 weeks remote, 4–10 weeks if onsite mobilisation is needed.
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.