ML Engineer, Applied AI

Lila Sciences
Cambridge, San Francisco
Workplace: OnsiteFull timeUSD 116,000 - 170,000 annuallyFunction: Data Science & Machine LearningSkills: ["Communication","Debugging","Experimentation","Collaboration","Evaluation design"]

Build and deploy applied AI models that close the gap between frontier model capabilities and customer scientific workflows. Train and post-train models (e.g., SFT and RL variants), design evaluation loops and experiments, and use traces/logs/customer context to debug failures. Partner with AI researchers and software teams to translate model improvements into end-to-end production workflows, supported by reusable adaptation and monitoring tooling.

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FursaFursa
Lila Sciences
Lila Sciences
2 days ago

ML Engineer, Applied AI

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build and deploy applied AI models that close the gap between frontier model capabilities and customer scientific workflows. Train and post-train models (e.g., SFT and RL variants), design evaluation loops and experiments, and use traces/logs/customer context to debug failures. Partner with AI researchers and software teams to translate model improvements into end-to-end production workflows, supported by reusable adaptation and monitoring tooling.
Location: Cambridge, San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Entry level

Key Responsibilities

  • •Bridge applied AI model capabilities to customer-specific scientific workflows by implementing last-mile production workflows.
  • •Post-train models using approaches such as SFT and RL (DPO, PPO/GRPO) to align model behavior with customer requirements and feedback.
  • •Build evaluation loops to measure model quality, reliability, and customer fit, and design experiments to improve performance across use cases.
  • •Feed customer learnings, data signals, and evaluation results back into the model improvement cycles.
  • •Debug model failures using traces, evaluations, customer context, and scientific feedback, and partner with software to integrate model behavior end to end.

Pay and Benefits

Salary: USD 116,000 - 170,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife InsuranceDisability InsurancePaid ParentalCommuter BenefitsMeal Allowance

Key Requirements

  • •Experience building, training, adapting, or evaluating machine learning models.
  • •Strong software engineering skills in Python and modern ML frameworks such as PyTorch, JAX, or TensorFlow.
  • •Design experiments, evaluation metrics, or test sets to assess model performance.
  • •Debug model behavior using data, traces, logs, and qualitative feedback.
  • •Work across research and engineering teams to move ML capabilities into usable systems.
Experience:Machine learningLarge language modelsAgentic AIProduction ML
Skills:CommunicationDebuggingExperimentationCollaborationEvaluation design
Tech Stack:PythonPyTorchJAXTensorFlowSFTRLDPOPPOGRPORLHFRetrieval-augmented generationTool useAgentic workflowsMoELLMsMultimodal models

Company Brief

Lila Sciences
Develops AI-driven platforms to accelerate drug discovery and biological research by integrating machine learning with chemical and biological data to predict molecular properties, streamline candidate selection, and enable faster therapeutic development.
Industry: Biotech
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
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