Senior / Staff Machine Learning Engineer, Applied AI
$180k - $298k • Cambridge, MA USA; San Francisco, CA USA • Full-time
Posted 24d ago
About the job
Lila Sciences is seeking a Senior / Staff Machine Learning Engineer to join their Applied AI organization. This role focuses on adapting and improving AI models for customer-specific scientific needs, bridging the gap between advanced model capabilities and real-world applications. You will be instrumental in transforming frontier AI models into reliable, evaluable workflows for customer contexts. The Applied AI team operates at the nexus of AI research, model engineering, and product deployment, collaborating with researchers and software engineers to integrate and refine Lila's models within product workflows. This position is ideal for individuals who want to specialize in model adaptation and evaluation, take ownership of complex technical challenges, and grow their scope within the company.
Responsibilities
- Adapt AI models to customer-specific scientific workflows.
- Perform post-training tasks using SFT and RL methods (DPO, PPO/GRPO) to align model behavior.
- Design and execute evaluation loops to assess model quality, reliability, and customer fit.
- Translate customer feedback and data signals into actionable model improvement cycles.
- Collaborate with AI researchers to integrate model advancements into usable capabilities.
- Work with software engineers to embed model behavior into end-to-end product workflows.
- Debug complex model failures using traces, evaluations, and customer context.
Requirements
- Minimum 1-2 years of hands-on experience in post-training (SFT, RL methods like DPO/PPO/GRPO) and evaluation system design.
- Strong software engineering skills in Python and modern ML frameworks like PyTorch.
- Demonstrated ability to quickly debug ambiguous, high-stakes model behavior using data, traces, logs, and qualitative feedback.
- Deep familiarity with large language models, multi-modal models, or agentic AI systems.
- Clear communication skills for translating customer needs and explaining complex model behavior.
Benefits
- Competitive base compensation with bonus potential.
- Generous early-stage equity.
- Comprehensive medical, dental, and vision coverage (U.S.).
- Employer-paid life and disability insurance (U.S.).
- Flexible time off with generous company-wide holidays (U.S.).
- Paid parental leave (U.S.).
- Educational assistance program (U.S.).
- Commuter benefits, including bike share memberships (U.S.).
- Company-subsidized lunch program (U.S.).
- International benefits tailored to region.