Top Tech Jobs & Startup Jobs in Boston, MA

Lead applied AI model post-training, evaluation, and production ML system development. Adapt models to customer-specific scientific workflows using SFT and reinforcement learning, build evaluation and monitoring systems, debug complex model behavior, collaborate with research and software teams, and mentor engineers. The role requires deep expertise in Python, PyTorch, LLMs, multimodal or agentic systems, and shipping reliable machine learning capabilities.

Owns go-to-market strategy, positioning, launches, offer development, case studies, and sales enablement for Lila Sciences’ life sciences product portfolio. The role translates AI, autonomous lab, and scientific capabilities into compelling narratives for biopharma and R&D buyers. It partners with Product, Commercial, Business Development, and Brand, synthesizes customer and competitive insights, and supports sales motions with major pharmaceutical accounts.

Owns strategic enterprise accounts across materials, chemicals, energy, and semiconductors. Responsibilities include developing multi-year account strategies, managing executive relationships, leading complex technical sales pursuits, negotiating large agreements, forecasting revenue, responding to technical RFIs and DDQs, and shaping commercial strategy. The role translates AI and autonomous laboratory capabilities into scientific and commercial value while partnering with product, science, software, robotics, legal, finance, and procurement teams.

Build and lead LILA’s supply chain demand-planning function, including order tracking, long-lead item management, demand signals, blanket-order sizing, inventory modeling, and delivery-capacity coordination. Partner with Procurement, Finance, Facilities, Lab Operations, suppliers, freight providers, and receiving teams to improve end-to-end visibility from order placement through installation and commissioning. Support ERP selection and implementation while resolving aging orders and escalating delivery risks.

Own lab equipment lifecycles, maintenance, calibration, installs, relocations, inventory, shipping, receiving, and vendor coordination. Support lab-space buildouts, safety and compliance activities, alarms, work-order systems, and operational process improvements. The role also onboards scientists to workflows, manages support tickets, mentors junior staff, and works hands-on across laboratory environments.

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.

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.

Design and build high-performance UI and APIs, manage database architecture, optimize systems for reliability and performance, and collaborate cross-functionally in a scientific context.