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Constructor TECH is seeking an ML Research Intern to advance agentic runtime systems within a deterministic control framework. You will contribute to building runtime layers that prevent hallucinations and enforce constraints, while exploring restorable compression and efficient KV-cache strategies.
The role targets systems-thinking individuals who enjoy the boring engineering—state machines, retries, idempotency, and serialization—applied to robust software around ML models.
Constructor’s mission is to enable all educational organisations to provide high-quality digital education to 10x people with 10x efficiency.
With strong expertise in machine intelligence and data science, Constructor’s all-in-one platform for education and research addresses today’s pressing educational challenges: access inequality, tech clutter, and low engagement of students.
Interns are NOT eligible for equipment and other benefits as the position is temporary.
The Reality
The frontier models are converging into commodities; the engine is no longer the differentiator. The scarcity in 2026 is not the model.
We are not looking for people to fine-tune Llama on toy datasets or write "better prompts." We are building the runtime systems that turn probabilistic token generation into reliable workers that finish 50-step tasks without spiraling. We are solving the math of multi-step reliability through engineering, not wishful thinking.
What You Will Solve
You will work on theAgentic Harness, treating the LLM as a component within a larger, deterministic control system. Your research will focus on:
Who We Are Looking For
We are looking forsystems thinkerswho happen to know ML, not the other way around.
Constructor fosters equal opportunity for people of all backgrounds and identities. We are led by a gender-balanced board committed to building a diverse and inclusive organisation where everyone can become their best self. We do not discriminate based on age, disability, gender identity, sexual orientation, ethnicity, race, religion or belief, parental and family status, or other protected characteristics. We welcome applications from women, men and non-binary candidates of all ethnicities and socio-economic backgrounds. We encourage people belonging to underrepresented groups to apply.