--- title: 'Applied ML Engineer at Sentient' canonical: 'https://feeny.ai/job/applied-ml-engineer-sentient-apac-20vwksxk3r1s' type: 'job' last_seen: '2026-10-13' --- # Applied ML Engineer at Sentient - **Company:** Sentient - **Location:** Apac, Singapore - **Employment:** full-time - **Work type:** remote - **Posted:** 2026-09-23 - **Last confirmed live:** 2026-10-13 - **Apply:** https://jobs.ashbyhq.com/sentient/c8354f11-556c-496c-8ef4-d6bd336a8f2d ## Job description Applied ML Engineer ## The Role We’re looking for an Applied ML Engineer to build systems at the intersection of machine learning research and production software. This is an end-to-end engineering role. You should be comfortable reading a research paper, identifying what is actually testable, building the smallest useful experiment, evaluating it rigorously, and turning the result into a production system that users can interact with. You’ll work across model evaluation, model internals, inference infrastructure, backend systems, and product interfaces. The goal is not simply to reproduce research. It is to turn promising methods into reliable, measurable, and usable products. ## What You’ll Do - Reproduce and evaluate research methods using open-weight and API-accessible models. - Design evaluation datasets, probes, scoring methods, baselines, calibration tests, and experiment harnesses. - Work directly with model weights, logits, hidden states, activations, model APIs, and inference infrastructure when required. - Build and extend our evaluation infrastructure, including runners, judges, persistence, experiment orchestration, and reporting. - Turn research workflows into product experiences, including experiment configuration, runs, traces, comparisons, reports, and review workflows. - Investigate how verification methods behave under model modification, including fine-tuning, merging, quantization, distillation, safety removal, and deliberate evasion. - Design controlled experiments that separate meaningful signals from artifacts or confounders. - Write clear technical reports that distinguish measured evidence, interpretation, and hypotheses. - Ship production-quality systems with APIs, background jobs, observability, testing, and documentation. ## What We’re Looking For - Strong Python engineering skills and hands-on experience with PyTorch and Hugging Face Transformers. - A strong understanding of ML evaluation, including dataset design, baselines, metrics, calibration, false positives, false negatives, statistical uncertainty, and reproducibility. - Ability to read ML research papers and implement methods from first principles rather than relying entirely on existing packages. - Experience building production software beyond notebooks, including APIs, asynchronous jobs, databases, logging, testing, and deployment. - Comfort working with open-weight models and understanding how modern LLM inference systems operate. - Ability to work across backend and frontend boundaries. Our product surface is primarily React/TypeScript, and you should be able to make complex experiments and results understandable to users. - Strong technical judgment about what experimental evidence does and does not support. For example, evidence that one model was derived from another is not necessarily evidence that it was directly trained on that model's outputs. - High agency and a strong sense of ownership. You are comfortable identifying problems, proposing solutions, and driving work forward without waiting for detailed instructions. - Comfortable working in a fast-moving startup environment where priorities can evolve quickly and individuals are expected to operate across functions. Useful Experience Experience in any of the following is a plus: - Model provenance, fingerprinting, watermarking, distillation detection, red-teaming, safety evaluations, or interpretability. - Activation and representation analysis, probing, model hooks, logits, hidden states, or other model-internals work. - Evaluation and inference infrastructure such as DSPy, LiteLLM, Temporal, Ray, vLLM, PostgreSQL/pgvector, or similar systems. - Next.js, React, TypeScript, data visualization, or experiment dashboards. - Running and serving open-weight models on GPUs and reasoning about latency, throughput, memory, precision, and cost tradeoffs. - Designing adversarial evaluations or testing systems against deliberate attempts to evade detection. What Success Looks Like in the First Six Months You will: - Reproduce at least one published model-provenance or verification method and clearly document its capabilities, assumptions, and limitations. - Build a repeatable model-verification runner with versioned inputs, artifacts, metrics, and reports. - Add at least one verification workflow to Construct and make it accessible through the Eldros UI. - Run controlled experiments across base models, fine-tuned models, merged models, quantized models, and known distilled models. - Improve our ability to understand when verification methods succeed, when they fail, and why. - Leave behind production-quality code, tests, tooling, and documentation that another engineer can confidently operate and extend. This Role Is Not - A pure research role where work ends with a paper or notebook. - A generic model-training or fine-tuning position. - A frontend-only or backend-only engineering role. - A role where benchmark scores are accepted at face value without understanding how they were produced. - A role for someone who wants to stay within a single layer of the stack. We are looking for someone who enjoys moving between research, experimentation, engineering, and product, and who cares about building systems that produce evidence people can actually trust. ## About Sentient ## Company Overview - **One-liner**: Sentient Foundation is a non-profit organization committed to building open-source Artificial General Intelligence (AGI), independent of single-entity control. - **Entity Type**: Private (Non-profit; Seed stage) - **Headquarters**: San Francisco, California, United States (with additional hubs in Greater New York City Area, Dubai, and Bengaluru, India) - **Founded**: 2024 - **Founders**: Himanshu Tyagi (Co-Founder & Co-CEO) and Ha Cuong (Co-CEO) ## Core Business - Primary industry/industries: Artificial Intelligence, Open-Source Software, AGI Research - Target customers: Researchers, engineers, developers, artists, thinkers, universities, labs, and independent collectives. The organization is community-driven and serves the broader open-source AI ecosystem rather than a traditional customer base. - Mission or purpose statement: To advance open-source AGI that is aligned with humanity and never controlled by a single entity. Core beliefs include that intelligence should be shared, not owned; AGI must be built in daylight; and open science, debate, and doubt create safer intelligence than secrecy. ## Products & Services - **ROMA (Reasoning & Orchestration for Machine Agents)**: An open framework for building multi-agent AI systems with structured reasoning and coordination. - **OML (Open, Monetizable, Loyal Models)**: A new primitive for distributing AI models that balances openness, control, and sustainability. - **ODS (Open Deep Search)**: A framework for building search-augmented reasoning systems using open-source models. - **Sentient Labs**: An open research initiative for conducting public research. - **Sentient Sparks**: A community-driven initiative designed to empower contributors in the Open AGI ecosystem through experimentation, collaboration, and idea exchange. - **Open AGI Summit**: A space for builders, founders, and researchers to discuss the future of open-source AI. ## Market Standing - **Valuation/Market Cap**: Not publicly available (non-profit entity). - **Key Metric**: Total Funding of $85M in a single Seed round (July 2, 2024). - **Notable Investors/Partners**: Founders Fund, Pantera Capital, Framework Ventures, and 23 other institutional investors. - **Growth Signals**: - Committed $42 million to advance open-source AGI, described as one of the largest commitments exclusively dedicated to this cause. - Expanding across Asia, building partnerships with universities, researchers, and local communities. - Employee count of 69 as of May 31, 2026, indicating steady growth since founding in 2024. - Actively hiring for 9+ open roles across engineering, business development, legal, and operations. ## Competitive Advantages - **Mission-Driven Non-Profit Model**: Unlike for-profit AI labs, Sentient is structured as a non-profit, ensuring its commitment to open-source AGI and independence from single-entity control is baked into its DNA. - **Open-Source Commitment**: The foundation is explicitly opposed to closed-door AGI development, positioning itself as a counterweight to proprietary AI giants. - **Comprehensive Open-Source Stack**: Offers a suite of frameworks (ROMA, OML, ODS) that cover multi-agent systems, model distribution, and search-augmented reasoning, creating an integrated ecosystem for developers. - **Strong Backing & Community**: $85M in seed funding from top-tier crypto and venture capital firms (Founders Fund, Pantera, Framework) provides significant runway for a non-profit. ## Strategic Focus - **Open-Source AGI Development**: The core priority is building and advancing open-source AGI through research, infrastructure, and community building. - **Community & Ecosystem Growth**: Initiatives like Sentient Sparks and the Open AGI Summit are designed to expand the contributor base and foster a global community of researchers and builders. - **Global Expansion**: Active expansion into Asian markets (Korea, India, and others) through university partnerships and local community engagement. - **Talent Acquisition**: Actively hiring for key roles (Director of Business Development, Director of Venture and Developer Relations, Senior Backend Engineer, etc.) to scale its operations and research capabilities across global hubs. ## Why Work Here - **Mission-Driven Impact**: The opportunity to work on one of the most ambitious and consequential projects in AI—building open-source AGI—with a clear ethical mandate that intelligence should be shared, not owned. - **Open & Collaborative Culture**: The foundation champions openness, collaboration, and public research, offering a stark alternative to the secrecy of many for-profit AI labs. - **Global & Remote-Friendly**: The organization is distributed across San Francisco, New York, Dubai, and Bengaluru, with many roles listed as remote-friendly, including engineering positions. - **Diverse Team Composition**: Actively seeks researchers, engineers, artists, thinkers, and community builders, creating a multidisciplinary environment. - **Early-Stage Growth**: With 69 employees and a significant funding commitment, Sentient is in a high-growth phase, offering early employees the chance to shape the organization and its technology from the ground up. ## Sources 1. [sentient.foundation](https://sentient.foundation/) 2. [sentient.foundation/about](https://sentient.foundation/about) 3. [jobs.sentient.foundation](https://jobs.sentient.foundation/jobs) 4. [tracxn.com](https://tracxn.com/d/companies/sentient/__ZIIZJhg1CP3W80i-o1ZJ35dGOwKA1D1vUdpR8j6zJzA) ## Other roles at Sentient - [Senior Backend Engineer](https://feeny.ai/job/senior-backend-engineer-sentient-bengaluru-gfs599ds5wy4) — Bengaluru, India - [Applied ML Engineer](https://feeny.ai/job/applied-ml-engineer-junction-remote-9w066h43mng9)