From Ema’s careers page.
About Ema
Ema builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboarding and benefits to IT support, invoice processing and payroll, so people can spend their time on work that needs them. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs.
We are backed by industry leading investors including Accel, Naspers/Prosus, Creaegis, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production. We ship real systems that run real business processes at scale.
The residency
The AI Residency is a 6-month builder role, not a research placement. Every engineer at Ema owns delivery end to end — from understanding the customer's problem to shipping, measuring and supporting it in production — and residents are held to the same bar. You won't be parked on one project: you'll contribute across several avenues, all toward one goal — creating real value and impact for our enterprise customers.
- Real production work. You work in the production codebase, on real customer problems and real production data. Recent residents have shipped agent harnesses, eval infrastructure, inference-cost reductions, PII redaction, automated QA pipelines and backend service hardening used by enterprise customers.
- End-to-end ownership. You take work from a problem statement to a shipped, measured result — design, build, test, launch, and the follow-through until it's reliable.
- Mentorship. A senior mentor, weekly 1:1s, regular reviews with your team, and exposure to the founders and engineering leadership.
- A path to full-time. Top-performing residents are offered full-time roles at Ema. Several of our engineers started as residents.
Choose your specialist track
Whichever track you choose, you own delivery end to end. The track decides where you go deepest.
- Backend. Go and Python services, APIs and data models for multi-tenant SaaS. Integrations that let agents take real actions in SAP, ServiceNow, Workday, Teams and Slack.
- AI/ML. Agents, harnesses and context engineering; evals and LLM judges calibrated against human labels; retrieval and memory; post-training (SFT, preference optimisation, RL) and distilling frontier behaviour into cheaper models.
- Systems & Infra. Kubernetes and cloud (Azure, GCP), regional deployments and data residency, model serving, observability, CI/CD and reliability at enterprise scale.
Where you'll contribute
Over the residency you'll work across several of these avenues, not just one:
- Customer deployments. Build and ship AI Employees for UK and European enterprises, working with the people whose problem it is.
- Platform and product. Turn patterns from the field into Ema's core product: new connectors, agent primitives, APIs and tooling.
- Quality and evaluation. Make agents measurably better: benchmarks from real workflows, failure mining, and the loop where production traces become training and eval data.
- Reliability and cost. Latency, uptime, inference cost and observability. Quality per pound is a metric we track.
- Trust and compliance. PII detection and redaction, data residency, and audit-ready evidence for customers under UK GDPR and the EU AI Act.
What we're looking for
- A builder's mindset and high agency. You find a way to ship rather than waiting for the blocker to clear, and you follow your work into production.
- Final-year undergraduates, MSc/MEng and PhD students, recent graduates and self-taught builders are all welcome. What matters is what you've built.
- Strong engineering fundamentals: data structures, algorithms, and clean code in Python, Go or a similar language. You're comfortable in a large production codebase.
- Real depth in your chosen track. Backend: services, APIs and data modelling. AI/ML: ML fundamentals, PyTorch, LLM systems or evals. Systems & Infra: Linux, containers, cloud and networking. One area you can teach us beats five you've touched.
- Honest measurement as a habit. You define what "done" and "better" mean before you build, and you'd rather kill your own feature with a clean experiment than ship it on a hunch.
- Clear communication. You can explain your work to engineers, customers and leadership, in writing and in person.
Show us what you've built
The best way to capture our attention is to point us to something you've built. Include a link — a GitHub repo, a live URL, a demo, or a write-up — with your application.
Logistics
- Location: Hybrid, from our London office.
- Term: 6 months, flexible start.
- Stipend: £ 2,500 - £ 3,000 / month.
- Right to work: You must have the right to work in the UK for the length of the residency.
Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.
