Top AI & Machine Learning Jobs

Design, build, and maintain high-traffic production LLM serving systems. Optimize throughput, latency, and cost for open-source language models by tuning inference engines and GPU execution stacks. Troubleshoot and improve inference performance, and collaborate to scale efficient, reliable inference infrastructure.

Develops, optimizes, and deploys lightweight machine learning models for edge AI and audio processing on embedded platforms, including FPGA and ASIC systems. Responsibilities include model compression, quantization, pruning, knowledge distillation, inference optimization, hardware-software integration, and system architecture collaboration. The role also provides technical leadership and mentorship while contributing to research publications, conferences, and open-source projects.

Leads Everlane’s data science and analytics team, delivering business insights, predictive models, experimentation, customer behavior analysis, and self-service analytics. Owns the data architecture and roadmap, evaluates new data and machine learning technologies, scales the data platform, and partners with stakeholders across marketing, digital product, and other business functions. Manages and develops data analysts, data scientists, and data engineers.

Develop, deploy, and industrialize machine learning solutions using structured and unstructured data across commercial and medical domains. Translate business challenges into data-driven solutions while ensuring data quality, governance, model validation, regulatory compliance, scalability, and reliability. Build end-to-end models from prototyping through production monitoring, collaborate with technical and business stakeholders, and apply predictive modeling, classification, regression, forecasting, and related analytics techniques.

Lead methodological strategy for AI-driven human behavior simulations during the sales process. Design audiences, stimuli, validation frameworks, proof-of-concept evaluations, and comparisons with traditional research methods. Translate business questions into rigorous simulation designs, explain statistical validity to senior stakeholders, support account executives and deployment teams, and convert field feedback into product priorities. Contribute to public methodology, accuracy frameworks, and validation publications.

Develops and manages AI and machine learning product roadmaps, leads cross-functional teams, oversees model development and deployment, and monitors model performance. Responsibilities include data preparation, exploratory analysis, LLM and NLP integration, governance, bias mitigation, compliance, risk management, stakeholder communication, product optimization, Agile delivery, and mentoring junior staff.

Leads robotics and AI engineering teams developing production-grade robotic systems, real-time computer vision models, ROS/ROS 2 control pipelines, and edge-deployed deep learning solutions. Owns vision pipeline architecture, object detection, segmentation, tracking, 3D pose estimation, data annotation, model training, MLOps, system integration, and performance targets. Also provides technical architecture guidance and manages engineering team capabilities.

Build and support practical AI solutions across GE Appliances by mapping business workflows, prioritizing use cases, developing prototypes and automations, testing with users, and creating reusable guides and playbooks. Lead workshops, office hours, and reskilling efforts to drive AI adoption. Collaborate with Digital Technology and AI Platform teams to align solutions with approved tools, while tracking adoption, time savings, quality improvements, and business impact.

Build and operate production machine learning systems focused on multilingual NLP, including entity linking, classification, event extraction, deduplication, and narrative analysis. Develop GPU-accelerated workflows, fine-tune transformer models, and create LLM features such as RAG pipelines and agents on AWS Bedrock. Establish evaluation frameworks, integrate ML services into Django and event-driven platforms, lead technical architecture discussions, and mentor team members.

Build and maintain mathematical optimization models for network planning, capacity allocation, routing, and freight operations. Develop production AI applications for process automation, document extraction, and decision support. Establish evaluation, validation, monitoring, and regression-testing frameworks for optimization and AI systems. Identify new business opportunities, prototype solutions, quantify impact, and scale successful initiatives. Partner with operations, pricing, sales, finance, engineering, and leadership to communicate trade-offs and deliver reliable analytical systems.