---
title: 'Senior / Staff Machine Learning Engineer, Applied AI at Lila Sciences'
canonical: 'https://feeny.ai/job/senior-staff-machine-learning-engineer-applied-ai-lila-sciences-cambridge-w8b902v8n99s'
type: 'job'
last_seen: '2026-10-16'
---

# Senior / Staff Machine Learning Engineer, Applied AI at Lila Sciences

- **Company:** Lila Sciences
- **Location:** Cambridge, MA / San Francisco, CA
- **Compensation:** $180k–$298k
- **Posted:** 2026-10-07
- **Last confirmed live:** 2026-10-16
- **Apply:** https://job-boards.greenhouse.io/lilasciences/jobs/4400741009

## Job description

## Your Impact at LILA

We are growing our Applied AI org and seeking a Senior / Staff Machine Learning Engineer, Applied AI with expertise in model post-training, evaluation, and production-oriented ML systems. You’ll shape how Lila’s AI models are adapted to customer-specific scientific needs, with a focus on turning frontier model capabilities into reliable workflows that can be evaluated, iterated and used in real customer contexts.

Applied AI sits at the intersection of AI Research, model engineering, and product deployment. The team partners closely with AI Researchers and Software teams to adapt Lila models to customer workflows, improve model quality through post training and driving how harness engineering shapes model behavior inside the product.

This is the right role for someone who wants to go deep on model adaptation and evaluation, take real ownership of hard technical problems, and grow into broader scope over time.

## What You'll Be Building

- Apply hands-on expertise to close the last-mile gap between Lila's model capabilities and customer-specific scientific workflows.
- Run post-training work using approaches such as SFT and RL (DPO, PPO/GRPO) to align model behavior with customer-specific requirements and feedback.
- Run evaluation loops that measure model quality, reliability, and customer fit.
- Turn customer learnings, data signals, and evaluation results into concrete model improvement cycles.
- Partner with AI researchers to translate model advances into reliable, usable capabilities.
- Work with Software to integrate model behavior into end-to-end product workflows.
- Debug complex model failures using traces, evaluations, customer context, and scientific feedback.

## What You'll Need to Succeed

- Minimum 1-2 years of hands-on post-training experience (SFT, RL methods such as DPO/PPO/GRPO) and evaluation system design, gained from having solved these problems many times before.
- Strong software engineering skills in Python and modern ML frameworks like PyTorch.
- A demonstrated ability to debug ambiguous, high-stakes model behavior quickly, using data, traces, logs, and qualitative feedback - the kind of judgment that only comes from having seen many failure modes before.
- Deep familiarity with large language models, multi-modal models, or agentic AI systems.
- Clear communication skills for translating customer needs into technical approaches, and for explaining complex model behavior to both technical and non-technical audiences.

Bonus Points For

- Experience adapting models for customer-facing or production workflows, ideally in scientific, technical, or data-intensive domains.
- Experience with RL post-training, such as RLHF, GRPO, or tool-augmented RL.
- Experience building evaluation harnesses, model monitoring, or quality dashboards.
- Experience training MoE architectures.
- A track record of mentoring engineers and being sought out as a go-to technical expert, rather than a people manager or strategy owner.

## Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range $180,000—$298,000 USD

## About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our [Candidate Privacy Policy](https://www.lila.ai/candidate-privacy-policy-notice).

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

## About Lila Sciences

## Company Overview
- **One-liner**: Lila Sciences is building the world’s first Scientific Superintelligence platform and autonomous lab, using AI to autonomously generate hypotheses, design and run experiments, and learn from results in real time across life sciences, chemistry, materials, energy, and defense.
- **Entity Type**: Private (Privately Held) – Series A, Seed, and Grant funding rounds
- **Headquarters**: Cambridge, Massachusetts, United States
- **Founded**: Not publicly available (first funding round was Seed in March 2025)
- **Founders**: Not publicly available (founded within Flagship Pioneering’s ecosystem)

## Core Business
- **Primary industry**: AI-powered scientific discovery and autonomous laboratory platforms
- **Target customers**: B2B – research organizations, biotech, pharmaceutical, energy, materials, aerospace, and defense companies
- **Mission**: “Scientific Superintelligence to solve humankind’s greatest challenges” – accelerating discovery across medicine, materials, energy, and defense

## Products & Services
- **LILA Platform (Scientific Superintelligence)**: An AI model and operating system that autonomously executes the entire scientific method – generating hypotheses, designing experiments, running them in physical labs, and learning from results in real time.
- **AI Science Factory™ Instruments**: Proprietary hardware and robotics that serve as the “body” of the platform, enabling automated experimentation at scale.
- **Domain-specific applications**: Tailored solutions for biotech (drug discovery, protein engineering), therapeutics (mRNA, antibodies, cell therapies), energy & environment (clean fuels, catalysis, critical minerals), advanced materials, chemicals, aerospace & defense, and oil & gas.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: Total funding – USD $550.7M (as of LinkedIn data)
  - Seed Round (March 2025): $200M led by Flagship Pioneering
  - Series A (September 2025): $235M led by Braidwell and Collective Global Management
  - Series A (November 2025): $115M led by NVentures (NVIDIA)
  - Grant (January 2026): $671,400 led by ARIA
- **Notable Investors/Partners**: Flagship Pioneering, NVIDIA (NVentures), Braidwell, Collective Global Management, ARIA
- **Growth Signals**: Named #25 on the 2026 CNBC Disruptor 50 List; headcount of 308 employees (monthly growth +10.6%); 122 active job postings; operates in 6 countries (US, UK, Canada, Poland, Spain, Germany)

## Competitive Advantages
- **Proprietary AI model** that consistently outperforms other models across scientific domains in complex analysis and reasoning.
- **Autonomous physical labs** that close the loop between AI hypothesis generation and real-world experimentation.
- **“Team of Teams” operating model** enabling startup speed at scale while maintaining radical transparency and high trust.
- **General platform approach** (inspired by Rich Sutton’s “Bitter Lesson”) rather than narrow domain-specific tools, allowing broad applicability.

## Strategic Focus
- Accelerating discovery across medicine, materials, energy, and defense
- Scaling the autonomous science platform to more industries and use cases
- Building “Scientific Superintelligence” that can tackle humanity’s greatest challenges
- Continued investment in AI research, robotics, and lab automation

## Why Work Here
- **Culture**: Emphasizes velocity, trust, curiosity, truth, and grit. “Think freely, prove precisely.” A high-trust, mission-driven environment where scientists and engineers work side by side.
- **Remote/Hybrid/Office**: Roles are listed in Cambridge, MA; San Francisco, CA; and London, UK. Physical lab presence suggests significant on-site work, but some roles may offer flexibility. Policy not explicitly stated.
- **Notable perks/engineering culture**: Opportunity to work at the frontier of AI and scientific discovery; collaboration with world-renowned experts; access to cutting-edge robotics and AI infrastructure; strong emphasis on learning and teaching (“generous teachers and eager learners”).

## Sources
1. [lila.ai](https://www.lila.ai/)
2. [lila.ai/about](https://www.lila.ai/about)
3. [lila.ai/open-roles](https://www.lila.ai/open-roles)
4. [LinkedIn - Lila Sciences](https://www.linkedin.com/company/lila-sciences)
5. [Greenhouse Job Board](https://job-boards.greenhouse.io/lilasciences/jobs/4246302009)

## Other roles at Lila Sciences

- [Contractor, P2P Specialist](https://feeny.ai/job/contractor-p2p-specialist-lila-sciences-cambridge-hqgazjbfnk8p) — Cambridge, MA
- [Product Manager, Chemistry AI Science Factory](https://feeny.ai/job/product-manager-chemistry-ai-science-factory-lila-sciences-cambridge-aqja2ckq6shw) — Cambridge, MA
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- [Senior Engineer II, Robotics Mechanical Design](https://feeny.ai/job/senior-engineer-ii-robotics-mechanical-design-lila-sciences-cambridge-pxv5xb3e5y22) — Cambridge, MA
- [Engineer II/ Senior Engineer, Robotics Platform Evaluation](https://feeny.ai/job/engineer-ii-senior-engineer-robotics-platform-evaluation-lila-sciences-cambridge-yjfk83r6maep) — Cambridge, MA
- [Principal Machine Learning Engineer, Applied AI](https://feeny.ai/job/principal-machine-learning-engineer-applied-ai-lila-sciences-cambridge-srsp3tf862dg) — Cambridge, MA / San Francisco, CA
- [Director, Product Marketing, Life Sciences](https://feeny.ai/job/director-product-marketing-life-sciences-lila-sciences-cambridge-vje1ygvbfcfk) — Cambridge, MA
- [Platform Scientist I/II, Functional Materials Instrumentation](https://feeny.ai/job/platform-scientist-i-ii-functional-materials-instrumentation-lila-sciences-q02rjs2f3cwm) — Cambridge, MA
- [Director, Enterprise Account Management, Physical Sciences](https://feeny.ai/job/director-enterprise-account-management-physical-sciences-lila-sciences-cambridge-h8s6rjtjrv6g) — Cambridge, MA