Senior Applied Scientist

Carbon Arc, Inc.; New York, Northern (NY, KY); Hybrid; USD 180,000 - 230,000; Full time

Benefits offered by this job

Remote work options

401(k) plan with employer contribution

Paid time off

Generous parental and family leave

Job summary

Carbon Arc, Inc. is seeking a Senior Applied Scientist to lead and expand research directions at the intersection of knowledge graphs, retrieval, and predictive analytics.

You will own end-to-end ML systems—from ideation and prototyping through production deployment—while inventing new ways to make data interoperable, valuable, and actionable at scale. This high-trust, high-impact role thrives on experimentation, rapid iteration, and building systems that have not existed before.

Qualifications

• 5+ years delivering machine learning, AI, or statistical modeling systems in production environments.
• MS or PhD in Computer Science, Statistics, or a related technical discipline.
• Deep proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
• Experience working with distributed data and compute technologies (e.g., Spark, Ray, Kubernetes).
• Strong background in unstructured data modeling, including embeddings, information retrieval, and LLM-based systems.
• Proven ability to take research prototypes and scale them into reliable, production-grade services.
• Clear, precise technical communication skills that support effective cross-functional collaboration.

Responsibilities

• Design and deploy machine learning pipelines for entity resolution, semantic linking, and data quality scoring across structured and unstructured data sources.
• Build downstream NLP and retrieval applications, including retrieval-augmented generation (RAG) and graph-based RAG over an enterprise knowledge graph.
• Apply graph learning, vector retrieval, and embedding-based similarity to unify analytics across text, metadata, and operational signals.
• Extend and operationalize temporal and causal modeling capabilities, representing events, sequences, and hierarchies within the knowledge graph.
• Apply temporal and causal models to forecasting, anomaly detection, and predictive analytics use cases.
• Maintain and evolve Carbon Arc's knowledge graph by enriching ontologies, improving linking logic, and optimizing downstream reasoning.
• Establish rigorous standards for model evaluation, monitoring, and lifecycle management in dynamic data environments.
• Collaborate closely with engineering teams on model design, API integration, and distributed inference workflows.
• Mentor scientists and engineers on experimental design, responsible AI practices, and scalable deployment.
• Contribute to intellectual property development, including internal frameworks, patents, and publications advancing data economics.

Skills

Python

PyTorch

TensorFlow

Distributed compute

Spark

Ray

Kubernetes

LLM-based systems

Unstructured data modeling

Technical communication

Education

MS or PhD in Computer Science/Statistics

Tools

Vector databases

Graph databases

Ontology-driven modeling

Job description

The Research & Intelligence team builds the machine learning and semantic intelligence capabilities at the core of Carbon Arc. Our work spans graph-based entity resolution, temporal and causal modeling, data valuation systems, and retrieval-augmented applications that operate over massive, heterogeneous data assets.

We are seeking a Senior Applied Scientist to lead and expand key research directions at the intersection of knowledge graphs, retrieval, and predictive analytics. In this role, you will own end-to-end ML systems—from research ideation and prototyping through production deployment—while inventing new ways to make data interoperable, valuable, and actionable at scale.

This is a high-trust, high-impact role for someone who thrives on experimentation, rapid iteration, and building systems that have not existed before.

What You'll Do

• Design and deploy machine learning pipelines for entity resolution, semantic linking, and data quality scoring across structured and unstructured data sources
• Build downstream NLP and retrieval applications, including retrieval-augmented generation (RAG) and graph-based RAG over an enterprise knowledge graph
• Apply graph learning, vector retrieval, and embedding-based similarity to unify analytics across text, metadata, and operational signals
• Extend and operationalize temporal and causal modeling capabilities, representing events, sequences, and hierarchies within the knowledge graph
• Apply temporal and causal models to forecasting, anomaly detection, and predictive analytics use cases
• Maintain and evolve Carbon Arc's knowledge graph by enriching ontologies, improving linking logic, and optimizing downstream reasoning
• Establish rigorous standards for model evaluation, monitoring, and lifecycle management in dynamic data environments
• Collaborate closely with engineering teams on model design, API integration, and distributed inference workflows
• Mentor scientists and engineers on experimental design, responsible AI practices, and scalable deployment
• Contribute to intellectual property development, including internal frameworks, patents, and publications advancing data economics

What You'll Bring

• 5+ years of experience delivering machine learning, AI, or statistical modeling systems in production environments
• MS or PhD in Computer Science, Statistics, or a related technical discipline
• Deep proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow
• Experience working with distributed data and compute technologies (e.g., Spark, Ray, Kubernetes)
• Strong background in unstructured data modeling, including embeddings, information retrieval, and LLM-based systems
• Proven ability to take research prototypes and scale them into reliable, production-grade services
• Clear, precise technical communication skills that support effective cross-functional collaboration

Nice to Have

• Experience designing and optimizing RAG or Graph-RAG architectures, including LLM evaluation and IR-driven optimization
• Hands-on expertise with vector databases, graph databases, graph algorithms, and ontology-driven modeling
• Experience with time-series forecasting, Bayesian inference, or causal modeling applied to economic, behavioral, or operational prediction
• Exposure to optimization, analytics, or modeling in data valuation or pricing systems

What We Offer

• Fully paid healthcare benefits (Medical, Dental, Vision)
• Remote work options
• 401(k) plan with employer contributions
• Paid time off
• Generous parental and family leave policies
• Challenging problems to tackle with a supportive, entrepreneurially driven team
• A strong work culture centered on integrity, excellence, truth, trust, and transparency

Location

Carbon Arc is headquartered in New York City and operates as a remote-first company. Team members are expected to travel for in-person onsite gatherings at least one week per quarter to collaborate, plan, and connect as a team.

Equal Opportunity Employer

Carbon Arc is an Equal Opportunity Employer and is committed to fair and equitable hiring practices. All hiring decisions are based on strategic business needs, job requirements, and individual qualifications. All candidates are considered without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, pregnancy, veteran or military status, citizenship status, or any other characteristic protected by applicable federal, state, or local law.

Accommodations

Carbon Arc is committed to providing reasonable accommodations throughout the hiring process for qualified individuals with disabilities. If you require an accommodation to participate in the application or interview process, please contact us at [e-mail] .