Agiloft

Data Scientist

Job Description

Position Overview

We are looking for an experienced Data Scientist to join our growing efforts in machine learning and generative AI. You will be part of our Data Science Team, working alongside ML Engineers, Knowledge Experts, and Developers to research, prototype, and develop machine learning features in production.


Job Responsibilities
  • Researching, prototyping, developing, and supporting production features that utilize machine learning and generative AI technologies, working closely with Data Scientists, ML Engineers, Knowledge Experts, and Engineers
  • Building, curating, and maintaining datasets for our analysis and our ML projects
  • Support the development and maintenance of our AI platform, aiding in both standard and custom AI model solutions for clients
  • Architect robust AI/ML features, addressing key scalability and performance issues. Provide expert recommendations on their usage and advocate for best practice patterns within the team
  • Engage in project initiatives and contribute to the planning process, ensuring alignment with project goals and team objectives
  • Play a role in educating internal stakeholders about our machine learning projects and their business implications
  • Other duties as assigned

    • Required Qualifications
  • 3-5 or more years of experience in a Data Scientist role
  • Fluency in Python and the associated Data Science stack (numpy, scipy, scikit-learn, pandas)
  • Fluency in at least one relational database language
  • You can communicate clearly and empathetically with developers, product managers, and UX designers to explain the abilities and limitations of ML systems
  • Ability to evaluate multiple models and approaches and make informed expert decisions
  • Experience with deep learning and genAI models, both third party and open source preferred
  • Ability to architect and deploy basic machine learning models in a production environment
  • Experience with a cloud-based infrastructure environment (AWS, GCP, etc.) and containerization technology (docker, Kubernetes)
  • Knowledge of machine learning model optimization, including the ability to advise on trade-offs and options
  • Familiarity with model drift, and the ability to monitor and respond appropriately in straightforward scenarios
  • Familiarity with at least one CI/CD tool and experience in modern principles of software development and version control

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