Build and maintain backend systems that power agent evaluation and continuous improvement, design data models, develop enterprise integrations, own features end to end, work directly with customers, debug distributed workflows and improve system reliability.
Compensation
Base salary is $120,000 to $180,000 USD annually. Visa sponsorship is available, including H-1B transfers, OPT, and O-1.
Responsibilities
Build and maintain backend systems that power agent evaluation and continuous improvement.
Design data models for evaluation datasets, experiment runs, agent traces, knowledge versions, findings, and customer-defined quality criteria.
Develop and support enterprise integrations, including authentication, OAuth, webhooks, incremental syncs, backfills, rate limits, retries, and monitoring.
Own features end to end, from technical design and implementation through deployment, observability, customer feedback, and iteration.
Work directly with customers to diagnose system failures and turn individual needs into reusable product capabilities.
Machine learning engineer leading the design and build of an agentic AI system to automatically resolve insurance claim denials for healthcare practices.
Compensation
The base pay range for this role is $150,000–$275,000 per year.
Responsibilities
Design and build the architecture for our agentic AI system that autonomously resolves insurance claim denials
Develop specialized AI agents for denial classification, root cause analysis, evidence retrieval, policy reasoning, and appeal generation
Implement multi-agent orchestration frameworks that coordinate complex workflows across research, decision-making, and document generation
Build and optimize RAG systems to retrieve relevant clinical documentation, billing records, and payer policy information
Create evaluation frameworks and feedback loops to continuously improve agent performance and reliability
Requirements
Nice to have: healthcare data experience
Nice to have: understanding of medical billing workflows
A core technical leadership role bringing state-of-the-art computer vision and multi-modal models from research into production-grade systems for AI-driven game experiences.
Compensation
Base Salary Range: We determine the base salary range for this role based on your primary work location: Zone A: $218,400 - $283,900 Zone B: $194,100 - $252,300 Zone C: $172,200 - $223,900
Responsibilities
Help set the technical vision and roadmap for computer vision and multi-modal AI models
Drive design and implementation of models for image and video understanding, generation, segmentation, detection, and dense prediction
Make sound decisions on model architecture, training strategy, data pipelines, and evaluation
Own the path from research prototype to production: training, fine-tuning, distillation, export, and serving
Collaborate directly with research scientists to translate novel CV and multi-modal model architectures into deployable implementations
The Senior Machine Learning Engineer (L5) will own end-to-end initiatives across the ML lifecycle, from problem formulation, feature engineering, and modeling to production serving and online A/B experimentation.
Compensation
Annual base salary range (excluding equity and bonus): $213,750—$225,000 USD
Responsibilities
Own end-to-end machine learning initiatives from problem formulation and offline evaluation to production deployment and online A/B testing
Build and iterate on multi-stage recommendation, retrieval, and contextual bandit models
Design intelligent notification orchestration, candidate ranking, and targeting systems
Develop production LLM pipelines, grounding workflows, and automated evaluation loops
Architect resilient, low-latency model serving services and real-time feature pipelines
Architecting, developing, and supporting enterprise-scale Agentic AI solutions using LLMs and RAG pipelines.
Compensation
Salary Range: $121,350.00 - $199,365.00
Responsibilities
Architecting, developing, deploying, and supporting enterprise-scale Agentic AI solutions
Build and implement scalable AI systems using Large Language Models (LLMs), retrieval-augmented generation (RAG) pipelines, model orchestration frameworks, Agentic frameworks, and secure API solutions
Ensure AI solutions align with enterprise security, governance, and compliance requirements
Collaborate cross-functionally with data scientists, software engineers, infrastructure teams, product teams, and business partners
Evaluate emerging technologies and contribute to enterprise AI roadmap
Seeking a Machine Learning Engineer/AI Researcher/Data Scientist to establish evidence for safer AI by designing safety benchmarks and experiments for multimodal large language models.
Compensation
The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
Responsibilities
Design and maintain safety benchmarks for large language and multimodal models
Define metrics and protocols that assess safety alongside model usefulness
Build reusable Python pipelines with versioned datasets and experiment tracking
Develop tools to discover failure modes through automated red-teaming
Investigate model failures and develop regression tests
Evaluate and prioritize AI initiatives based on business value, technical feasibility, risk, and scalability
Track and communicate AI portfolio progress, investment, realized benefits, and risk
Partner with the Corporate AI Enablement Center on governance for AI solutions
Requirements
Bachelor's degree in Engineering, Computer Science, Data Science, Information Systems, a related field, or a combination of education and equivalent experience.
Nice to have: Experience in industrial manufacturing, aerospace, or another regulated engineering environment
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