Factored (backed by Andrew Ng's AI Fund and deeplearning.ai) helps leading tech companies select, upskill, and build world-class data science, machine learning and AI engineering teams much faster and more cost effectively. Our engineers have been personally vetted, educated, and mentored by some of the most talented and recognized AI educators and engineers from Silicon Valley, Stanford University and deeplearning.ai.

Factored 

Recruitment

Lead Talent Operations to build top AI & Data teams for clients.

• Continue to build and scale our Talent Operations function.
• Lead Factored's Talent team, inspiring high performance.
• Lead team-level and cross-functional initiatives to improve sourcing and matching processes.
• Drive cross-functional collaboration between Talent, Engineering, and Sales teams.
• Implement workflows and tools to improve the end-to-end Talent Journey.
• Collaborate with Marketing to fill the candidate pipeline.
• Work cross-functionally to build a data-driven Talent Operations function.
• Stay abreast of AI & Data industry issues and trends.

Head of Talent Operations

Machine Learning Engineer

Develop and deploy advanced machine learning models integrating retrieval and generation capabilities.

• Design, develop, and optimize RAG models that combine retrieval-based and generation-based approaches to solve complex problems.
• Enhance the performance of RAG models through innovative algorithmic techniques and fine-tuning.
• Fine-tune and adapt LLMs for specific tasks and domains within the RAG framework.
• Work with cross-functional teams to integrate RAG models into production environments and ensure seamless deployment.
• Utilize machine learning methods and advanced techniques like LLMs to create effective AI solutions.
• Design, deliver, and maintain features such as predictive analytics, automated risk assessments, intelligent data extraction, and personalized insights.
• Write well-designed, maintainable, and testable code. Create clear and comprehensive design documentation.
• Prioritize customer needs and experiences in all development efforts.
• Designed and developed frameworks for GenAI products, such as search interfaces, bots, and summarizers.

Machine Learning Engineer (RAGs)

Data Engineer

Lead data engineering team in dynamic startup environment for Factored

• Lead data engineering team at Factored
• Drive growth and retention initiatives
• Collaborate with AI training team for continuous learning

Director of Data Engineering

• Responsible for planning, implementing, directing, and administering all aspects of the human resources function for the Mid-Atlantic Region
• Provide day-to-day management of the Employee Relations team

Data Engineer (Spark)

Analytics Engineer

• Design, develop, and maintain data pipelines, data models, and ETL processes to support data integration, transformation, and aggregation.
• Work closely with stakeholders to understand their data requirements and translate them into scalable analytics solutions.
• Ensure data quality, accuracy, and consistency by implementing data validation, cleansing, and monitoring techniques.
• Identify and implement optimizations to improve the efficiency and performance of data pipelines and analytics processes.
• Build and test code using CI/CD best practices.
• Perform transformations using state-of-the-art data to create data models for consumption, often leveraging data stack tools like DBT.&nbsp;&nbsp;
• Write and maintain data catalogs and definitions.
• Collaborate with data scientists and analysts to implement data-driven models, algorithms, and visualizations.


• Design, build, and maintain data pipelines
• Integrate data from different sources
• Utilize data processing frameworks
• Set up and manage data storage systems
• Monitor data pipelines and infrastructure
• Lead or support development of proofs of concept
• Employ Apache Airflow or Dagster for managing data workflows
• Work with SQL and NoSQL databases
• Utilize Kubernetes for managing containerized data applications

DataOps Engineer

Data Analyst

Analyze and interpret data to drive strategic decisions for global AI engineering solutions.

• 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.

Factored Jobs in New York City