Referso Jobs

Research Assistant

Generalist · Posted Nov 9, 2026

Open

Boston, Massachusetts, United States
Full-time · Entry
0–3 years

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Research Assistant

Generalist · Posted Nov 9, 2026

Open

Boston, Massachusetts, United States
Full-time · Entry
0–3 years

Apply with Referso

Staff Research Engineer, Hardware Intelligence

Nominal · Posted Nov 9, 2026

Open

New York, New York, United States
On-site
Full-time · Staff
8+ years

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Setting the research agenda for Hardware Intelligence, building agents that reason over hardware context, and leading the post-training of AI models.

Responsibilities

Set the research agenda for Hardware Intelligence: pick the problems, place the bets, and define what winning looks like each quarter.
Figure out how to store and represent hardware context, so agents reason over telemetry, test campaigns, requirements, designs, and simulations instead of retrieving them.
Teach agents to work the tools engineers already use, from CAD to simulation to analysis software, through computer use.
Connect simulation to the physical world: calibrate simulations against measured results, and use simulations to plan and explain tests.
Build distributed intelligence: collections of agents that coordinate across programs, fleets, and teams.

Requirements

Nice to have: post-training at a frontier lab
Nice to have: computer-use agents
Nice to have: multi-agent systems
Nice to have: knowledge representation
Nice to have: scientific ML

Skills

ML research RL reward models

Data Scientist - Sciences

Vantive · Posted Jul 7, 2026

Open

Oakdale, Minnesota, United States
Hybrid
Full-time · Senior
$128K–$160K per year
5+ years

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The Data Scientist will be responsible for supporting the Global R&D Sciences team to design experiments and analyze data optimizing experimental efficiency and minimize the risks of accuracy, precision and errors and generate quantitative insights.

Compensation

$128,000 to $160,000 annually

Responsibilities

Supporting R&D projects and products through input on designs of laboratory testing and/or the analyses of existing data.
Devising new approaches to complex problems through adaptations and modifications of standard technical principles, e.g., DMAIC, experimental DOE, and Hypothesis testing.
Assure the use of appropriate statistical rigor in testing and data analyses.
Designing experiments and assisting others with design of experiments
Determining variables assessed versus those remaining fixed

Requirements

Degree in engineering
sciences
math
statistics
Nice to have: Python

Skills

Statistical rigor Design of Experiments (DOE)DMAIC Hypothesis testing

Staff Research Engineer, Agent Evals & Post-training - UK

Nominal · Posted Nov 9, 2026

Open

London, England, United Kingdom
On-site
Full-time · Staff
8+ years

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Lead the design and implementation of agent evaluation and post‑training pipelines for Nominal’s AI‑native hardware platform.

Responsibilities

Build eval suites for agents and internal tools
Invent new benchmarks for physical engineering data
Benchmark agents against frontier agents
Build eval infrastructure and regression gates
Turn evals into reward signals and training data

Requirements

Nice to have: Frontier lab experience
Nice to have: Published benchmarks
Nice to have: Open‑weight model deployment
Nice to have: Test reliability engineering

Skills

ML engineering Evaluation of LLM or agent systems Post‑training (fine‑tuning, RL, distillation)Statistical rigor Hardware engineering AI coding agents Claude Code

Senior AI Developer

ClickUp · Posted Nov 6, 2026

Open

Remote, United States
Remote
Full-time · Senior
5+ years

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Senior AI Engineer responsible for building and evolving AI evaluation systems, core agent harness, and scalable AI platform services at ClickUp.

Responsibilities

Design, build, and own ClickUp's AI evaluation system, including golden datasets, LLM-as-judge and automated scorers, regression detection, and quality tracking across AI features.
Build and evolve the core agent harness, and the AI that performs well on those evals, partnering closely with product and engineering to define what "great" looks like.
Build self‑improvement loops where agents modify other agents or prompts, rerun evals, and iterate automatically.
Benchmark new models as they're released and own model selection, routing, and fallback strategies across providers (e.g., OpenAI, Anthropic, Google, open-weight).
Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models.

Requirements

Nice to have: Background in data science
Nice to have: Applied science
Nice to have: Machine learning engineering
Nice to have: Eval tooling
Nice to have: Braintrust

Skills

Python Go

Director-Advanced Analytics

AT&T · Posted Nov 3, 2026

Open

Dallas, Texas, United States
On-site
Manager
$211K–$316K per year

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Lead the development and implementation of advanced causal measurement and experimentation frameworks to drive marketing and business decisions at AT&T.

Compensation

Our Director-Advanced Analytics jobs earn between $210,600.00 - $316,000.00 USD Annual.

Responsibilities

Establish AT&T’s Marketing Causal Truths
Develop AT&T’s causal measurement architecture
Build scalable causal models
Embed causal evidence into forecasting and optimization
Lead Marketing’s experimentation ecosystem

Skills

causal measurement RCTs geo experimentation synthetic controls difference-in-differences regression discontinuity Bayesian approaches causal machine learning Directed Acyclic Graphs

Research Assistant

Research Assistant

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Staff Research Engineer, Hardware Intelligence

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Data Scientist - Sciences

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Staff Research Engineer, Agent Evals & Post-training - UK

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Senior AI Developer

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Director-Advanced Analytics

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Statistical rigor jobs

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