Principal Machine Learning Engineer, Applied AI

lilasciences; Cambridge; On-site; GBP 191,000 - 254,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Life and disability insurance

Flexible time off

Parental leave

Educational assistance

Commuter benefits

Lunch program

Job summary

Lila Sciences is seeking a Principal Machine Learning Engineer, Applied AI to lead post-training, evaluation, and production ML systems for customer-specific scientific workflows. You will transform frontier model capabilities into reliable, end-to-end pipelines.

You will collaborate with AI Researchers and Software teams, build evaluation loops, and mentor engineers, shipping robust models across medicine, materials, and energy domains.

Qualifications

• Minimum 2–3 years of hands-on post-training experience and evaluation system design.
• Strong software engineering skills in Python and PyTorch.
• Ability to debug and ship complex model behavior in production environments.

Responsibilities

• Lead post-training efforts (SFT, PPO/GRPO) and align model behavior with customer needs.
• Build and run evaluation loops to measure quality and reliability.
• Collaborate with AI researchers and software teams to integrate models into end-to-end product workflows.
• Mentor engineers and share patterns for model adaptation, evaluation, and deployment.

Skills

Post-training ML

Python

PyTorch

Evaluation design

Leadership across teams

Tools

RL methods

Evaluation harnesses

Job description

Your Impact at LILA

We are growing our Applied AI org and seeking a Principal Machine Learning Engineer, Applied AI with deep 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 a high‑impact senior IC role for someone who brings deep, hands‑on expertise in model post‑training, evaluation, and production ML systems, built over many years of solving this exact class of problem.

What You'll Be Building

• Apply deep, hands‑on expertise to close the last‑mile gap between Lila's model capabilities and customer‑specific scientific workflows.
• Lead post‑training efforts using approaches such as SFT and RL (DPO, PPO/GRPO) to align model behavior with customer‑specific requirements and feedback.
• Build and run evaluation loops that measure model quality, reliability, and customer fit, using patterns you've refined across many prior projects.
• 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.
• Mentor engineers and share reusable patterns for model adaptation, evaluation, and deployment, drawing on lessons learned across a long track record of shipping ML systems.

What You’ll Need to Succeed

• Minimum 2-3 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.
• Experience leading technical work across research and engineering teams.
• 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

• 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 membership for office based employees
• and company subsidized lunch program.

International Benefits

• Full‑time employees outside the U.S. receive a comprehensive benefits program tailored to the region.

USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range

$252,000 - $336,000 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,