ML Engineer - Demand Geneneration / Research / Engineering

Deccan AI is  AI training, evaluations and Enterprise AI solutions startup headquartered in the Bay Area. We are founded by IIT Bombay, IIM Ahmedabad and ex-Google alumni, and work with some of the top AI frontier labs in the world. Backed by Prosus Ventures and A91 we are expanding the team in US, San Mateo.

We are looking for an ML Engineer – Demand Generation / Research / Engineering to build intelligent systems that leverage machine learning, data science, and AI to drive business growth and demand generation.

This role sits at the intersection of applied research, machine learning engineering, and business applications. You will explore and develop ML-driven solutions for lead generation, audience intelligence, personalization, conversion optimization, and automated growth workflows.

You will work on translating business challenges into scalable ML solutions, combining experimentation, research, and engineering to build systems that deliver measurable business impact.

The ideal candidate is a hands-on ML engineer with strong technical depth, a research-oriented mindset, and the ability to apply ML beyond traditional use cases.

• Research, design, and develop ML models and intelligent systems for demand generation, lead scoring, conversion prediction, and growth optimization.

• Build and deploy scalable ML pipelines for data processing, feature engineering, model training, evaluation, and inference.

• Explore and implement ML techniques for audience segmentation, behavioral modeling, personalization, and predictive analytics.

• Experiment with LLMs, generative AI, recommendation systems, and advanced ML techniques to develop intelligent business applications.

• Translate research ideas and business requirements into production-ready ML solutions.

• Design data pipelines and experimentation frameworks to support targeting, campaign optimization, and performance measurement.

• Collaborate with cross-functional teams across Engineering, Research, Product, and GTM to identify opportunities for AI-driven automation and optimization.

• Evaluate emerging ML techniques, conduct experiments, and continuously improve model performance, scalability, and reliability.

• Establish robust evaluation frameworks to measure model effectiveness and business impact.

• 3–7 years of experience in Machine Learning Engineering, Applied Research, Data Science, or related technical roles.

• Strong programming skills in Python and experience with ML frameworks such as PyTorch or TensorFlow.

• Strong understanding of machine learning fundamentals, statistical modeling, optimization, and model evaluation.

• Hands-on experience building ML pipelines, deploying models, and working with large-scale datasets.

• Experience applying ML to real-world problems such as predictive modeling, recommendation systems, personalization, user modeling, or intelligent automation.

• Ability to independently explore research problems, design experiments, and translate findings into scalable engineering solutions.

• Strong problem-solving skills with the ability to work across research, engineering, and business-oriented challenges.

• A builder's mindset with strong ownership, curiosity, and a willingness to experiment and iterate quickly.