Lead the design, evaluation, and deployment of the production photogrammetry pipeline, including feature detection, SfM, MVS, mesh reconstruction, and infrastructure for scale.
Drive integration of newer 3D approaches like gaussian splats and foundation models, optimizing for speed, accuracy, and robustness.
Mentor engineers, take on 1–2 direct reports in the first year, and shape how the team uses AI across the SDLC.
Dronedeploy powers field teams with robotics and AI, offering a reality capture platform that combines robotic automation, AI agents, and a unified system for industries like construction, energy, and agriculture. The company is remote-first, recognized as a Best Place to Work in the SF Bay Area and one of America's Great Places to Work, with a culture rooted in innovation, impact, and support for growth.
Develop and improve AI/ML solutions for autonomous driving and future sensing objectives.
Apply techniques like unsupervised pre-training, imitation learning, and reinforcement learning to perception problems.
Collaborate cross-functionally to integrate models into production and evaluate sensing tradeoffs across real-world scenarios.
General Motors is redefining mobility through human-centered design, creating vehicles and experiences that aim to make driving safer, smarter, and more connected. With a global footprint and a culture focused on innovation and inclusion, GM’s diverse team brings collective passion for engineering, technology, and design to deliver on a vision of Zero Crashes, Zero Emissions, and Zero Congestion.
Architect the migration of the existing compiler flow into MLIR, defining dialects, passes, and lowering strategies.
Build conversion paths between MLIR and Mythic’s custom low-level IR to keep both flows operational during migration.
Define validation infrastructure within MLIR, including interpretation or execution paths for simulation and debugging.
Mythic is building the future of AI computing with breakthrough analog technology that delivers high performance at low power and cost. They have raised over $100M from world-class investors and secured multi-million-dollar customer contracts across multiple markets.
Own the full ML lifecycle, taking projects from ideation to production, including feature engineering, model selection, deployment, and model observability and evaluation.
Translate business needs into ML solutions, gathering product requirements and translating them into robust ML system design requirements.
Build recommendation and ranking systems, architecting and launching ranking and recommendation infrastructure from scratch, initially via integrated off-the-shelf models, and evolving to targeted and customized solutions in the long term.
Affinity's Relationship Intelligence platform empowers dealmakers to find, manage, and close more deals. It has more than 3,000 customers worldwide and is backed by Silicon Valley firms, with $120M raised, also receiving Inc. and Fortune Best Workplaces awards.
Act as a trusted advisor to customers, building relationships with technical and business stakeholders.
Advise on GenAI and ML best practices, giving product demos to technical and business stakeholders.
Partner with product and engineering teams to drive the product roadmap and spearhead new opportunities within existing accounts.
Arize AI is transforming the world by helping teams monitor, troubleshoot, and optimize their AI systems with its AI & Agent Engineering observability and evaluation platform. They are a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base.