Top AI & Machine Learning Jobs

Lead AI sector diligence workstreams: conduct expert interviews, build quantitative and qualitative analysis, and produce investor-facing reports. Own end-to-end project execution, collaborate with a Sector Lead, and perform primary research with executives, customers, and domain experts to inform investment decisions.

Lead development, tuning, and optimization of incrementality and attribution models for podcast advertising. Build, test, and refine statistical models on large datasets, collaborate with product and data teams, translate findings into actionable insights, and improve measurement methodologies to quantify ad impact.

The Principal Machine Learning Infrastructure Researcher will design and model performance for ML systems using Lightmatter technology while leading a small team and publishing research findings.

As a founding Machine Learning Engineer, you will improve core models, optimize LLM inference, develop data pipelines, and ship features directly to users.

The Principal LLM Application Engineer will develop and optimize Large Language Models, lead projects, evaluate performance, and collaborate across teams to enhance AI capabilities in cybersecurity.

Design, build, and deploy production ML systems that combine structured clinical/EHR data with computer vision outputs. Own model calibration, interpretability, monitoring, drift detection, retraining workflows, and regulatory documentation. Partner cross-functionally, mentor engineers, and translate clinical questions into reliable, production-grade ML solutions.

Forum Ventures seeks a founder to build startups that remove vendor lock-in in edge AI: developing edge runtimes, compiler abstractions, intelligent inference routing, and unified operational planes for mixed NPU fleets. The founder will build product, hire and lead teams, validate markets, and work with Forum’s venture studio for funding, GTM, and operational support to reach early traction.

Drive strategy and execution for simulation and neural reconstruction products: conduct customer discovery, define roadmaps, translate technical AI and simulation needs into scalable features, track success metrics, collaborate with engineering and GTM, and support launches. Role includes frequent customer interaction and on-site visits.

Lead the Identity squad to design, implement, and scale identity resolution (clustering/entity resolution) pipelines and algorithms at US scale. Own architecture, cost/performance optimization across Dagster, Spark, and Iceberg, build observability and evaluation frameworks, extend identity into audience construction, and lead cross-functional roadmap and mentoring for the squad.

Use AI platforms (Claude, ChatGPT, etc.) to analyze large datasets, improve data quality, build AI-assisted workflows and PoCs, partner with Product/Data/Engineering, document findings, and support enterprise search intelligence improvements.