2 days ago

AI Resident

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Own an end-to-end, production-based ML/agent project: write the proposal, build the system, design evaluation, ship behind a gate, and report results—including what didn’t work. Work in the production codebase with a senior mentor and real production data, tackling problems across inference-time harnesses, post-training (SFT/RL/reward modeling), environments and rewards, data engines, evaluation, and efficiency/quality-per-dollar.

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Own one hard problem end to end, from proposal through build, evaluation, gated shipping, and a write-up of true outcomes.
•Implement harnesses and inference-time work, including context/tool/skill design, orchestration, and deciding where extra inference compute is worthwhile.
•Drive agent post-training efforts such as SFT, preference optimization, and RL on real agent tasks with verifiable rewards.
•Create training/evaluation environments from enterprise workflows, including fixtures, simulated users, defenses against reward hacking, and reliable grading.
•Advance evaluation and efficiency by building behavior-level benchmarks with calibrated LLM judges and improving routing/ensembles/caching/small-model specialization.

Pay and Benefits

Salary: USD 4,000 monthly

Key Requirements

•Demonstrated depth in ML or agent systems; no specific degree required.
•Solid ML fundamentals and strong engineering, with experience in Python and PyTorch and the discipline to ship in a production codebase.
•Depth in at least one area such as post-training (SFT/DPO/GRPO-family RL), reward modeling or LLM judges, agent/tool-use systems, retrieval and memory, or evaluation design.
•Statistical literacy to design and interpret experiments correctly (e.g., understanding sampling at a given seed).
•A habit of honest measurement—running clean experiments to validate ideas rather than relying on hunches.

Experience:Agentic AIMachine learningReinforcement learning

Skills:Statistical literacyHonest measurementEngineering discipline

Tech Stack:PythonPyTorchVLLMSGLangSFTDPOGRPOTRLVeRLOpenRLHF

Company Brief

Ema Unlimited

Builds an enterprise agentic AI platform (Ema) that creates AI employees to automate complex workflows across customer support, HR, finance and other functions, with a focus on security, compliance, and model fusion for high accuracy.

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Funding: Series A

Headquarters: San Francisco, United States

Founded: 2023

Glassdoor: 1.5

Website LinkedIn Glassdoor

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Ema Unlimited

2 days ago

AI Resident

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Own one hard problem end to end, from proposal through build, evaluation, gated shipping, and a write-up of true outcomes.
•Implement harnesses and inference-time work, including context/tool/skill design, orchestration, and deciding where extra inference compute is worthwhile.
•Drive agent post-training efforts such as SFT, preference optimization, and RL on real agent tasks with verifiable rewards.
•Create training/evaluation environments from enterprise workflows, including fixtures, simulated users, defenses against reward hacking, and reliable grading.
•Advance evaluation and efficiency by building behavior-level benchmarks with calibrated LLM judges and improving routing/ensembles/caching/small-model specialization.

Pay and Benefits

Salary: USD 4,000 monthly

Key Requirements

•Demonstrated depth in ML or agent systems; no specific degree required.
•Solid ML fundamentals and strong engineering, with experience in Python and PyTorch and the discipline to ship in a production codebase.
•Depth in at least one area such as post-training (SFT/DPO/GRPO-family RL), reward modeling or LLM judges, agent/tool-use systems, retrieval and memory, or evaluation design.
•Statistical literacy to design and interpret experiments correctly (e.g., understanding sampling at a given seed).
•A habit of honest measurement—running clean experiments to validate ideas rather than relying on hunches.

Experience:Agentic AIMachine learningReinforcement learning

Skills:Statistical literacyHonest measurementEngineering discipline

Tech Stack:PythonPyTorchVLLMSGLangSFTDPOGRPOTRLVeRLOpenRLHF

Company Brief

Ema Unlimited

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Funding: Series A

Headquarters: San Francisco, United States

Founded: 2023

Glassdoor: 1.5

Website LinkedIn Glassdoor