Junior analyst partnering with stakeholders to solve business problems using SQL, Python/R for data analysis, delivering executive recommendations, and building BI dashboards. Requires recent STEM grad with internship experience in quantitative analysis.

As a Senior AI Enablement Engineer, you will design and build foundational AI infrastructure, tooling, and workflows to enhance efficiency across the organization. This role involves building scalable AI systems, partnering with various teams, and driving the adoption of AI-powered workflows.

Lead analytical efforts for servicing initiatives, partnering with product, operations, and engineering teams to drive insights, optimize recoveries/collections strategies, design A/B tests, and build BI pipelines. Requires 8+ years in analytics, proficiency in SQL/Python, and experience with large datasets.

Builds and maintains scalable data models and pipelines using Snowflake, dbt, and Databricks to support analytics for patient intake funnel. Leads BI solutions, self-service tools, and best practices with 5+ years experience, advanced SQL, and cross-functional collaboration.

Builds end-to-end ML systems for autonomous insurance underwriting, finetuning LLMs, closing feedback loops with underwriter data, and deploying production models. Requires 4+ years ML experience, Python proficiency, and production LLM expertise.

Builds ML infrastructure, models, and platforms to enable AI-powered features for developers handling massive datasets. Requires 5+ years backend experience, production ML deployment, and expertise in LLMs, RAG, distributed systems, and cloud platforms.

Builds and scales data pipelines for video generation models, including ingestion, annotation via MTurk/Prolific, preprocessing, and curation using Python, AWS, Kubernetes. Requires 3+ years in ML/data engineering, PyTorch experience, and cross-functional collaboration.

Builds and improves core AI agent systems for retrieval, tool use, document understanding, and orchestration in production. Designs evals, analyzes traces, and iterates based on real enterprise workflows using Python and LLM expertise.

Builds production-ready agentic AI systems including runtimes, orchestration, reliability, observability, and integrations with LLMs/APIs. Requires strong backend experience, shipped agent/LLM systems, and production reliability expertise.

Build and iterate on AI agents for customer interactions, outperforming humans in complex scenarios. Requires 5+ years experience with Python/TypeScript, systems debugging, and model evaluation/integration.

Drives strategic initiatives in product pricing and monetization through analytics, operations, and cross-functional partnerships. Requires 2-5 years experience in strategy/ops, SQL proficiency, and strong communication skills.

Embeds with marketing teams to identify high-leverage workflows, build custom AI tools/agents/automations, coach marketers on AI integration, and scale transformations for self-sufficiency. Requires 5+ years experience building transformative AI solutions and strong coaching skills.

Builds and scales Generative AI platform infrastructure using advanced ML techniques. Requires deep expertise in large-scale model training, deployment, and optimization on cloud platforms.

Senior Data Scientist develops ML models and features using device, network, and behavioral data for fraud prevention and identity verification. Requires 6+ years experience, Master's in quantitative field, Python/SQL proficiency, and production ML deployment expertise.

Designs threat models and experiments for agentic AI security risks, builds prototypes with fine-tuned models and analysis tools, and turns research into scalable product defenses. Requires MS/PhD in CS/ML, production coding skills, and security mindset.

Build and deploy scalable AI agents for customer support that handle complex interactions across industries like finance and healthcare. Requires 5+ years experience with Python and TypeScript, focusing on system reliability and model integration.

Develops and deploys vision-language-action models and world models for autonomous robot finishing tasks in construction. Owns full lifecycle from data collection via teleoperation to edge deployment on Jetson hardware, requiring strong ML on robotics experience.

Leads design and implementation of scalable security data pipelines and API-first services to deliver real-time security telemetry for enterprise customers. Requires 8+ years in data engineering, distributed systems, and languages like Java, C++, or Rust.

Builds and trains large-scale multimodal agentic models involving reasoning, planning, coding, and tool calling. Requires strong ML foundations, PyTorch expertise, and experience with distributed training on massive datasets.

Leads applied AI investments, owning technical direction for high-impact AI products from design to production deployment. Requires 8+ years AI/ML experience, Python expertise, foundation models, LLM patterns, and evaluation systems.

Leads architecture of AI agents that convert natural language to production full-stack apps, driving multi-provider LLM strategies, tool integration, evaluation standards, and cross-team AI initiatives. Requires deep LLM expertise, prompt engineering, and scalable systems design.

Leads development of agentic AI systems for public sector, including guardrails, data processing, and fleet orchestration for federal datasets. Mentors engineers, defines technical strategy, and communicates with stakeholders to ensure reliable, secure solutions.

Develops advanced Vision-Language-Action models for robotaxi scene understanding, detecting hazards and enabling safe driving. Leads data strategies, post-training of large models, and deployment using PyTorch and production ML pipelines. Requires MS/PhD in CS and deep learning expertise.

Build benchmarks, datasets, and evaluation systems to measure and improve AI model quality for fraud, identity, and risk judgment tasks. Collaborate across research, engineering, and product to drive rigorous experimentation and iteration in high-stakes environments.

Research Engineer designs evaluations, studies model failures, and builds research loops to improve AI agents for high-stakes fraud detection and judgment tasks. Requires ML training experience, experimental rigor, and strong engineering skills in adversarial environments.

Designs and implements AI agents that transform natural language into production-ready full-stack applications using state-of-the-art LLMs. Integrates multiple LLM providers, orchestrates workflows, and continuously improves agent performance through data analysis and experimentation. Requires TypeScript proficiency and hands-on LLM experience.

Senior ML Engineer optimizes inference for voice AI models (STT, TTS, speech-to-speech) using engines like TensorRT-LLM and SGLang on GPUs. Requires 5+ years ML engineering with serving/inference expertise, Python/PyTorch proficiency, and production ML experience.

Conducts foundational research in spatial AI for residential construction, developing novel models using reinforcement learning, computer vision, LLMs, and 3D geometry. Requires 5+ years software engineering with 2+ years LLM experience, Master's degree, and expertise in PyTorch and RAG systems.

Leads financial data workflows, transforming raw data into actionable insights via SQL, Python, and BI tools. Builds models, dashboards, and reports for executives while partnering with engineering teams. Requires 4-7 years experience, expert Excel/SQL, and finance fluency.

Lead data scientists design and execute experiments like A/B tests and causal inference to inform product and go-to-market decisions, build predictive models for forecasting and segmentation, and manage a team of analysts while shaping company strategy.

Owns end-to-end data strategy including sourcing, curating, and structuring multimodal data (text, video, images) for AI model training. Requires strong Python, SQL, large-scale processing, and ML-first mindset with LLM experience.

Build and validate an AI Chief of Staff prototype that automatically extracts, sorts, assigns, and follows up on meeting action items using LLMs, RAG, and agentic systems. Requires strong GenAI, NLP, Python backend, and productivity tool integration experience.

Conducts fundamental research on data-efficient ML architectures, including bootstrapped program synthesis and self-synthesizing learning systems. Requires Master's in ML/math, PyTorch fluency, and research experience.

Software Engineer enabling production AI workloads on new hardware platforms through porting, benchmarking, stress testing, and performance optimization. Requires 5+ years in ML systems, distributed training, PyTorch, and RDMA/NCCL expertise.

Builds scalable backend systems and deploys ML models in production for client engagements, working embedded with top clients 3-4 days/week in New York. Requires 8+ years experience in ML engineering, Python, LLMs, cloud platforms, and client-facing work.

Staff Data Scientist designs statistical frameworks and conducts robust analysis to validate safety-critical AI systems for autonomous vehicles. Delivers data-driven insights to engineering teams and leadership, scaling pipelines for petabyte-scale driving data analysis. Requires MS/PhD in quantitative field and expertise in Python, SQL, and statistical methods.

Develops systems for LLM interpretability and deterministic governance by working directly with model weights, activations, and architectures. Implements mechanistic interpretability techniques like activation patching and control vectors for enterprise policy enforcement in production.

Leads research in agentic AI and LLMs, developing models for enterprise reasoning, autonomous agents with tool use, and production systems. Requires PhD, expertise in LLM training/fine-tuning, agent systems, and technical leadership.

Designs and builds scalable batch/streaming data pipelines for identity verification products, owning end-to-end data initiatives using cloud-native tech. Requires 5+ years data engineering with Spark, AWS, Python/SQL; streaming/orchestration experience preferred.

Leads architecture and implementation of healthcare payer data integrations (EDI X12, HL7/FHIR) and scalable pipelines for AI/ML systems. Requires 5+ years data engineering experience with payer data and team leadership.

Staff Data Scientist owns end-to-end development of ML and Generative AI solutions for the RiskOS fraud prevention platform, from data exploration and modeling to production deployment and monitoring. Requires 6+ years experience in data science with fraud/risk focus, Python/SQL proficiency, and GenAI expertise.

Develops and improves Codex AI agents for real-world software engineering tasks, focusing on performance, reliability, and integration with research and product teams. Requires strong Python, ML/LLM experience, and skills in evaluation, prompting, and debugging production failures.

Builds and maintains machine learning models, applies statistical analysis, and delivers insights that guide product, go-to-market, and business decisions. The role requires 3+ years of data science experience, strong Python and SQL skills, and a bachelor's degree in a quantitative or computer science field.

Leads end-to-end delivery of complex healthcare analytics projects, translating business questions into data insights, managing client relationships, and driving team performance. Requires 8+ years in healthcare analytics, proficiency in SQL/Python/R, and strong project management skills.

Builds and owns production ML platform systems, turning AI research into reliable, scalable features. Partners with CTO on prototyping, observability, and end-to-end deployment of AI capabilities. Requires 3+ years experience with Python and modern ML frameworks; onsite in NYC.

Designs evaluation measures, harnesses, and datasets to assess risks from frontier AI systems, including dangerous capabilities testing. Collaborates with agencies, publishes methodologies for policymakers; requires 3+ years ML experience and publications in generative AI.

The role optimizes large-scale distributed training and inference for foundation models, focusing on profiling, parallelization, memory efficiency, and productionization. It requires strong Python skills, multi-GPU training experience, and expertise in modern ML architectures.

Develops post-training pipelines, RLVR experiments, synthetic data generation, and large-scale LLM evaluation systems to enhance frontier language model performance in tool use, agentic behavior, and reasoning. Requires strong ML experience, coding skills, and research background.

Designs, develops, and optimizes core runtime infrastructure for distributed AI training and inference using PyTorch-based stack. Requires 8+ years in systems engineering, deep learning runtimes, Python/C++, and multi-node GPU workloads.

Build in-house tooling for post-training custom ML models using advanced techniques like RL and finetuning. Requires deep expertise in transformer training, PyTorch distributed systems, parallelism strategies, GPU performance optimization, and HPC platforms.