Top Tech Jobs & Startup Jobs

Develop and apply machine learning methods for protein engineering, including generative design, property prediction, candidate selection, active learning, and sequence or structure modeling. Collaborate with experimental scientists to translate biological objectives into computational problems, evaluate model generalization, interpret wet-lab results, and improve design-test-learn workflows for therapeutic biomolecules.

Develop BioML systems that encode and evaluate mechanistic biological reasoning. Analyze single-cell, perturbation, proteomics, imaging, and genetic data; design experimental campaigns; build outcome-verifiable benchmarks; and connect computational predictions with experimental decisions. The role requires rigorous evidence assessment, uncertainty interpretation, reproducible analysis, and collaboration with ML engineers, experimental scientists, and platform teams.

Design and fabricate prototype devices and test structures for novel materials research. Develop and troubleshoot thin-film deposition recipes and cleanroom processes, including lithography, etching, and metrology. Characterize films and devices using profilometry, ellipsometry, SEM, and electrical probing. Integrate fabrication into automated, high-throughput workflows and collaborate with materials scientists, device physicists, systems engineers, and machine learning scientists to execute rigorous fabrication campaigns.

Design end-to-end workflows for Lila’s scientific software platform, translating complex scientific, operational, and AI-native capabilities into intuitive experiences. Partner with product, engineering, science, and operations teams; conduct research and usability testing; prototype AI interactions; and contribute scalable design patterns and systems across the Lila App.

Own OT security engineering for laboratory instruments, automation, and building systems. Translate OT security architecture into controls (segmentation, identity, PAM, PKI), build detection and response, validate vendor integrations, run vulnerability and lifecycle management, and mentor engineers while partnering with SOC, OT engineering, and lab operations.

Build and improve applied AI models for scientific customer workflows. Responsibilities include model post-training, evaluation loop development, experiment design, debugging model behavior, and integrating AI capabilities into production software. The role collaborates with AI researchers and software engineers to adapt models, create reusable tooling, and translate customer feedback into model improvements.

The Machine Learning Engineer will design and implement ML pipelines and productionize models, collaborating with scientists and engineers on scalable systems.

Develops reproducible Python-based data analyses and bioinformatics pipelines for life sciences experiments. Translates wet-lab workflows and scientific questions into validated analytical requirements, integrates workflows with data lake and AI systems, and builds reusable analysis modules. Collaborates with scientists, automation specialists, software engineers, and ML engineers while identifying data, LIMS, and workflow gaps and documenting methods, assumptions, and results.

Lead end-to-end multimedia production across video, photography, graphics, animation, and scientific storytelling. Partner with scientists, engineers, product, sales, recruiting, communications, and facilities teams to translate complex concepts into compelling visual content. Manage production timelines, reviews, asset delivery, metadata, versioning, archiving, and reusable templates. Develop visual storytelling strategies and use AI-powered tools to increase production speed while maintaining quality.

Lead an 8–10-person engineering team building LILA’s AI-native application platform, including chat, agents, artifacts, and integrations with laboratory workflows and ML pipelines. Define technical strategy, oversee end-to-end product delivery, ensure reliability and security, collaborate with scientists and cross-functional partners, mentor engineers, and represent the company’s applied-AI work externally.