Factor Funding Company

Data Analyst

• Collect, clean, and transform raw data from various sources into structured datasets for analysis.
• Perform thorough data analysis using statistical techniques and tools to identify patterns, correlations, and trends.
• Develop and implement data models, algorithms, and visualizations to present findings in a clear and concise manner.
• Monitor and track key performance indicators (KPIs) to assess the effectiveness of strategies and initiatives.
• Identify opportunities for process improvements and develop data-driven solutions.
• Collaborate with cross-functional teams to understand business requirements and provide data-driven insights and recommendations.
• Transform complex, multi-source datasets into strategic insights that drive decision-making for global organizations.
• Design analytical frameworks, build models, and shape metrics guiding product direction, operational efficiency, and business growth.
• Fuel experimentation, guide strategic priorities, and provide leaders with insights for confident decision-making.

Explore Senior Data Analyst, Tableau at Factor Funding Company. Review requirements and application details.

Senior Data Analyst, Tableau

Machine Learning Engineer

• Design, develop, and optimize Retrieval-Augmented Generation (RAG) models for complex, real-world client problems.
• Improve RAG model performance through advanced algorithms, innovative techniques, and fine-tuning.
• Collaborate with client Data and Engineering teams to build robust machine learning infrastructure.
• Work with client leadership to identify and leverage transformative AI/ML opportunities.
• Fine-tune and adapt large language models for specific tasks and domains within the RAG framework.
• Deploy RAG models into production environments and ensure seamless integration and long-term success.
• Apply advanced machine learning techniques, including LLMs, to develop client-tailored AI solutions.
• Write clean, maintainable, scalable, documented, and testable code.
• Prioritize user experience and customer needs in product development.
• Design and develop GenAI product frameworks, including search interfaces, chatbots, and summarization tools.
• Build and implement machine learning models and algorithms supporting client growth and success.
• Provide technical leadership in identifying and evaluating AI/ML opportunities.

Explore Senior Machine Learning Engineer – RAGs at Factor Funding Company. Review requirements and application details.

Senior Machine Learning Engineer – RAGs

• Design and implement multi-stage recommendation pipelines, including Candidate Generation (Retrieval), Ranking, and Re-ranking/Filtering stages
• Develop and fine-tune machine learning and deep learning models for personalized recommendations using Collaborative Filtering, Matrix Factorization, Two-Tower Networks, and Deep Learning such as Deep & Cross Networks
• Build and optimize two-stage retrieval architectures using Approximate Nearest Neighbors vector search engines such as Faiss, Pinecone, or Milvus
• Implement real-time scoring and inference pipelines using feature stores such as Feast or Hopsworks and scalable serving frameworks such as Triton, TorchServe, or Ray Serve
• Establish A/B testing frameworks, offline evaluation metrics including NDCG, MAP, and Recall@K, and real-time monitoring for model performance and business metrics
• Optimize recommendation system latency and throughput using quantization, caching, and hardware acceleration
• Own recommendation pipelines end-to-end from experimentation to production deployment

Explore Senior Machine Learning Engineer – Recommender Systems at Factor Funding Company. Review requirements and application details.

Senior Machine Learning Engineer – Recommender Systems

Analytics Engineer

• Design, develop, and maintain data pipelines, data models, and ETL processes for data integration, transformation, and aggregation.
• Collaborate with stakeholders to understand data requirements and translate them into scalable analytics solutions.
• Implement data validation, cleansing, and monitoring techniques to ensure data quality, accuracy, and consistency.
• Optimize data pipelines and analytics processes for improved efficiency and performance.
• Build and test code using CI/CD best practices.
• Perform advanced data transformations and create data models, often using tools such as dbt.
• Write and maintain data catalogs and definitions.
• Collaborate with data scientists and analysts on data-driven models, algorithms, and visualizations.

Explore Senior Analytics Engineer, Snowflake at Factor Funding Company. Review requirements and application details.

Senior Analytics Engineer, Snowflake

Manager

• Own end-to-end project delivery from scope definition to final release.
• Define measurable goals and deliverables with senior leadership.
• Serve as the primary client contact throughout the project lifecycle.
• Drive agile delivery through sprint planning, release calendar management, go/no-go coordination, and iterative plan adaptation.
• Lead engineering teams, remove impediments, run standups and steering meetings, and maintain team velocity.
• Identify and resolve conflicts and develop contingency plans for technical and operational risks.
• Develop and manage project plans, timelines, and resource allocation for large-scale initiatives.
• Maintain executive-level visibility through steering committee meetings and recommend strategic pivots.
• Integrate client requirements into the broader roadmap.
• Establish and refine PMO methodologies, agile frameworks, and organizational best practices.
• Analyze project performance data, profitability, ROI, and lessons learned.

Explore Delivery Manager at Factor Funding Company. Review requirements and application details.

Delivery Manager

• Build and automate CI/CD pipelines for machine learning models and data workflows using GitHub Actions, GitLab CI, or Jenkins.
• Architect and manage containerized microservices and orchestration platforms for ML workloads using Docker and Kubernetes (EKS, GKE, AKS).
• Implement and manage ML lifecycle, tracking, and versioning tools such as MLflow, DVC, or Kubeflow.
• Provision, configure, and maintain ML cloud infrastructure using Infrastructure as Code tools like Terraform.
• Establish monitoring, alerting, and logging systems for deployed models using Prometheus, Grafana, or Arize to track data drift, model performance, and operational health.
• Collaborate with data scientists and software engineers to transition ML models from experimental scripts into secure, low-latency, scalable production APIs.
• Design, build, and maintain infrastructure, pipelines, and tools enabling seamless machine learning deployment and operation across enterprise environments.
• Own ML workflows end-to-end, from automated training and versioning to production monitoring and continuous integration.

Explore Senior MLOps Engineer at Factor Funding Company. Review requirements and application details.

Senior MLOps Engineer

Account Executive

• Identify and engage decision-makers at enterprise companies, driving the full sales cycle from lead generation to contract closure while developing long-term account strategies.
• Build trusted advisor relationships with key stakeholders, understanding their data and AI talent needs, and positioning Factored AI as the ideal partner.
• Develop and maintain a robust pipeline, leveraging CRM tools to track opportunities, accurately forecast revenue, and ensure disciplined deal progression.
• Lead contract negotiations with a focus on creating win-win outcomes, securing long-term partnerships, and fostering ongoing client trust.
• Stay informed about industry trends, competitive landscapes, and enterprise challenges in AI, ML, and data engineering.
• Partner with marketing, customer success, and internal talent teams to optimize customer outcomes and drive continuous improvement.
• Lead net-new client acquisitions and close multi-million-dollar enterprise deals to drive ARR growth.

Explore Enterprise Account Executive at Factor Funding Company. Review requirements and application details.

Enterprise Account Executive

AI Engineer

• Architect, design, and implement backend Python systems integrating LLMs via the Model Context Protocol (MCP), ensuring services are scalable, secure, and production-ready.
• Implement stateful agentic architectures and reasoning loops for multi-step AI workflows using frameworks such as LangGraph.
• Build, deploy, and manage cloud-native AI applications on AWS, including Bedrock, Lambda, and ECS.
• Champion Spec-Driven Development (SDD) and Context-Driven Development (CDD) for deterministic, structured model outputs.
• Architect semantic memory layers and build advanced RAG pipelines using vector databases.
• Implement AI security guardrails, boundary controls, and Human-in-the-Loop approval flows for compliance, privacy, and safety.
• Monitor application health with APM, LangSmith, and Phoenix; track agent trajectories and LLM performance metrics and resolve performance issues.
• Onboard teams, build reusable prompts, automate repetitive workflows, and drive organization-wide adoption of AI-native developer tools such as Claude Code and Cursor.
• Collaborate with ML Engineers, product managers, and cross-functional teams to understand requirements and deliver valuable AI features.
• Communicate technical architecture and trade-offs to stakeholders.
• Raise engineering standards through code review and knowledge sharing.

Explore Senior AI Engineer at Factor Funding Company. Review requirements and application details.

Senior AI Engineer

• Architect agent task decomposition into actionable sub-tasks
• Develop Plan-and-Execute and ReAct patterns
• Design short-term memory systems for long-running tasks
• Create interfaces between LLMs and external software, databases, and APIs
• Standardize function calling, legacy-system interaction, and sandboxed Python execution
• Implement error handling and self-correction
• Build evaluation frameworks measuring trajectory success, efficiency, and safety
• Set up monitoring to visualize agent processes and diagnose workflow failures
• Implement guardrails and Human-in-the-Loop checkpoints for high-stakes decisions
• Own intelligent automation systems end-to-end from prototyping through production deployment

Explore Senior Machine Learning Engineer – LLMs, Agentic Workflows at Factor Funding Company. Review requirements and application details.

Senior Machine Learning Engineer – LLMs, Agentic Workflows

Sales Engineer

• Lead technical discovery calls with prospects, surfacing requirements, constraints, and success criteria across data engineering, ML, data science, analytics, and AI engineering use cases.
• Design and present ML, AI, and Data Science system architectures live with clients, including RAG, agentic workflows, LLM evaluation pipelines, model serving infrastructure, and end-to-end MLOps.
• Translate ambiguous business problems into scoped, deliverable engagements by defining solution approaches, identifying risks, sizing effort, and shaping statements of work alongside Account Executives.
• Serve as the deal-side technical authority, defending architectural choices and challenging suboptimal designs.
• Build technical proposals, reference architectures, and proof-of-concept plans.
• Partner with delivery leadership to hand off won deals, ensuring scope, assumptions, and technical context transfer accurately.
• Develop and maintain reusable solution patterns, demos, and reference implementations.
• Stay current on the AI/ML landscape and apply that knowledge in client conversations.
• Provide feedback to product, delivery, and marketing on prospect needs and offering improvements.
• Represent Factored externally through webinars, technical content, conference conversations, and select customer events.

Explore Sales Engineer at Factor Funding Company. Review requirements and application details.

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