Machine Learning Engineer

Company Description

WeLaunch partners with early-stage B2B, SaaS, and AI startups to drive fast and effective go-to-market (GTM) strategies. We act as a plug-and-play GTM team, enabling founders and revenue leaders to build pipeline efficiently through strategies like LinkedIn and email outreach, outbound systems, and marketing initiatives such as webinars and community-led growth. WeLaunch integrates directly with businesses to provide immediate execution without extended hiring processes or excessive costs. Our adaptable model supports startups at different growth stages, helping them validate strategies, streamline sales funnels, and achieve consistent pipeline generation.

Role Description:

This is a full-time, on-site role for a Machine Learning Engineer located in Bengaluru. The Machine Learning Engineer will be responsible for designing and implementing machine learning models, developing neural networks, analyzing statistical data, and optimizing algorithms. The role also involves collaborating with team members to build robust solutions that address company and client needs and staying up-to-date with the latest advancements in machine learning and AI technologies.

Key Responsibilities

• Design, develop, and deploy prediction/forecasting models.
• Build end-to-end ML pipelines covering data collection, feature engineering, model training, evaluation, and production deployment.
• Analyze large datasets and identify predictive signals.
• Continuously monitor, improve, and optimize model accuracy and performance.
• Integrate ML models into scalable production systems.
• Conduct research and experimentation to improve forecasting methodologies.
• Collaborate with product and engineering teams to enhance the overall prediction ecosystem.
• Explore alternative and non-traditional data sources where relevant.

Required Qualifications

• Strong experience in Machine Learning, Statistical Modeling, and Data Analysis.
• Hands-on experience building prediction or forecasting models.
• Deep understanding of the complete ML lifecycle.
• Experience deploying and maintaining ML models in production environments.
• Strong proficiency in Python and common ML frameworks.
• Ability to evaluate model performance and implement continuous improvement strategies.

Preferred Qualifications

• Experience in sports prediction, weather forecasting, financial markets, prediction markets, or similar domains.
• Research experience, published papers, or contributions to research-driven projects.
• Familiarity with prediction market platforms such as Polymarket.
• Interest in or willingness to explore numerology, astrology, gematria, or alternative data-driven approaches to forecasting.

What We're Looking For

Someone who can think beyond model building and help architect, refine, and scale a sophisticated prediction system capable of evolving over time.