Top Tech Jobs & Startup Jobs in Boston, MA

Design and operate GPU/accelerator infrastructure and inference platforms for large ML models. Build Kubernetes-based scheduling, multi-tenant GPU sharing, autoscaling, model serving, IaC (Terraform/Helm) for EKS, CI/CD for model artifacts, observability for latency and throughput, and cost/capacity optimization across heterogeneous accelerators.

Design, develop, and deploy scalable laboratory automation and workcells. Partner with scientists, hardware, controls, and software teams to translate experimental goals into robust automated workflows, implement machine vision and sensor-based detection, perform FMEAs, troubleshoot and optimize systems, and lead technical teams to ensure safety, reproducibility, and regulatory alignment.

Lead training, adaptation, evaluation, and productionization of Lila's AI models for scientific customer workflows. Build evaluation loops, design experiments, debug model failures, integrate model improvements into product workflows, and create reusable tooling for model adaptation, evaluation, and deployment while collaborating across research and software teams.

Lead go-to-market and messaging for Lila's life science product portfolio (RNA/DNA design, medicinal chemistry). Define positioning, launch plans, and evidence strategies; create technical content and case studies; enable sales and customer success; and align product, commercial, and brand teams to drive adoption and measurable business impact.

Coordinate rollout and administration of lifecycle systems (PLM/QMS), support deployment and commissioning workflows, maintain operational documentation and asset lifecycle visibility, and drive cross‑functional execution for AISF platform deployments and the Blueprint systems program.

Conducts high-throughput formulation and materials characterization, including rheological, thermal, chemical, tensile, peel, and shear testing. Prepares reagents, samples, and consumables; follows SOPs; records experimental data; troubleshoots workflow issues; and improves shift-based processes. The role involves wet-lab handling of polymers, coatings, adhesives, paints, and elastic materials while collaborating with scientists and engineers across life sciences and physical sciences.

Develop and deploy machine learning models and active-learning workflows for complex fluids and soft-matter formulations. Connect composition, microstructure, processing, and bulk fluid properties, incorporate mesoscale/continuum simulation outputs, partner with experimental teams, and communicate model behavior and recommendations to cross-functional collaborators to accelerate formulation discovery.

The Senior Software Engineer will develop systems for scientific workflows, APIs, and applications, collaborating across teams to enhance performance and reliability in production environments.

Build and apply machine learning models and active-learning workflows for polymers and soft materials. Connect formulation, processing history, morphology, and simulations to predict mechanical, thermal, and processing-sensitive properties. Partner with experimental teams to align models with lab throughput, interpret uncertainty, and prioritize formulation decisions.

The Staff Engineer will lead technical direction on data infrastructure, focusing on ingestion frameworks, storage architecture, and orchestration to support scientific workflows. Responsibilities include mentoring, ensuring reliability, and collaborating with cross-functional teams to establish coding standards and data integrity.