Location: Remote (open to India, Pakistan, Eastern Europe, LATAM) (HR32079)
Salary Range: 2000 - 3500 USD/month, depending on region and experience
Work Schedule: Monday - Friday, 9:00 AM to 5:00 PM, flexible with overlap in US EST hours
NOTE: INDEPENDENT CONTRACTOR POSITION
Company Overview:
Sagan is an exclusive membership community for top executives, founders, and CEOs seeking to hire and maximize the impact of international talent. We bridge the gap between global talent and US-based businesses, connecting candidates from vibrant regions like Latin America, the Philippines, India, Pakistan, Bangladesh, and Africa with leading American companies. Sagan provides a high-performance remote work environment, ensuring access to world-class opportunities for top-tier professionals.
About the Company:
Sagan represents a dynamic investment group seeking to build out AI-powered tools and processes to increase efficiency, support data analysis, and drive automation across portfolio companies.
Position Overview:
The AI/ML Engineer will be responsible for hands-on development and deployment of AI and automation solutions. This role involves building models, integrating tools, analyzing data, and ensuring scalable, reliable solutions.
Key Responsibilities:
Develop and implement AI/ML models, automation tools, and analytics dashboards.
Research, test, and integrate AI tools to support portfolio company operations.
Conduct data analysis and due diligence support for investment opportunities.
Collaborate with internal stakeholders to understand technical requirements.
Provide documentation and light training for teams adopting new tools.
Qualifications:
Strong technical background in Python, ML frameworks, and data analytics.
Experience with AI/ML model deployment and API integrations.
Ability to identify and implement automation opportunities.
English proficiency sufficient for internal collaboration (40–60/100).
Nice-to-Haves:
Familiarity with NLP, large language models, or generative AI APIs.
Experience working with investment or consulting firms.
Knowledge of data engineering pipelines.
