Top Tech Jobs & Startup Jobs in Boston, MA

As an FPGA Engineer, you will design, implement, and test FPGA-based systems, deploy RTL code, and collaborate with ASIC engineers on chip verification and prototype development.

The Photonics Design Engineer will design and optimize optical components, lay out circuits, analyze test data, and support prototype development.

The role involves designing, testing, and validating mixed-signal ASICs for photonic circuits, collaborating across functions, and supporting manufacturing and testing processes.

As an AI Lead, you will deploy models on prototype hardware, develop algorithms, work with hardware engineers to refine architecture, and support market strategy development.

The Photonics Test Engineer will operate automated wafer-level test capabilities, write scripts, perform hands-on measurements, and prepare data for the integrated photonics team.

Lead cross-functional integration of integrated photonics, electronics, hardware, and AI teams to produce system prototypes. Drive system-level models, simulations, requirements, verification planning, program execution, customer-facing technical briefings, and proposal support.

Lead cross-disciplinary integration of photonics, electronics, hardware, and AI teams to deliver working prototypes. Drive system-level models and simulations, translate requirements into scoped work, manage schedules, risks, and resources, and serve as technical/programmatic customer contact while supporting proposals and program reporting.

Lead cross-disciplinary integration of integrated photonics, electronics, hardware, and AI to deliver working prototypes. Drive system-level models, schedules, risk management, customer briefings, and proposal support for government and commercial programs.

Design, implement, and test FPGA systems and embedded firmware to support chip verification and prototype development. Deploy RTL (Verilog/VHDL) and embedded C/C++ to FPGA SoCs, bring up PCBs and peripheral interfaces (ADC/DAC/memory), perform FPGA trade studies, and collaborate with ASIC and AI teams to iterate prototypes and scale FPGA infrastructure.

The Machine Learning Architect will deploy models on prototype hardware, adapt algorithms for new environments, and collaborate with hardware engineers to define architecture based on practical insights.