Machine Learning Engineer

We're looking for a curious and resilient Machine Learning Engineer who thrives in a culture of experimentation and rapid iteration. Our ideal candidate doesn't just apply AI concepts - they're excited to push boundaries, challenge assumptions, and learn from both successes and failures. If you believe that the only true failure is not experimenting quickly, we want you on our team. Responsibilities : - Embrace a "fail fast, learn faster" mentality, aiming for a 20-30% success rate in your ideas and experiments. - Continuously optimize our experimentation process, making it faster, more efficient, and more insightful. - Apply AI concepts to solve business problems, with a focus on rapid prototyping and iterative improvement. - Leverage SQL and data manipulation tools to work with complex datasets, exploring unconventional approaches. - Apply statistical methods, machine learning algorithms, and data visualization techniques to perform exploratory data analysis, embracing unexpected insights. - Build and interpret models using tools like PySpark and ML-Flow, constantly testing new approaches and parameters. - Write clean, well-documented code that facilitates collaboration and hence faster iteration. - Continuously evaluate and enhance existing models, viewing each iteration as an opportunity to learn and improve. Requirements : - Proficiency in rapidly prototyping and testing ideas using large, complex datasets and SQL. - Expertise in implementing and iterating on machine learning models and algorithms, with a focus on quick experimentation cycles. - Strong programming skills in Python and/or SQL, with an emphasis on writing code that facilitates easy modification and testing. - Experience in leveraging data visualization techniques to quickly interpret and communicate experimental results. - Ability to swiftly deploy and iterate on AI solutions in cloud environments. - Passionate about experimentation and embracing failure, viewing setbacks as valuable learning opportunities. - Excellent written and verbal communication skills, able to articulate the value of experimentation and rapid iteration to stakeholders. - Thrives in ambiguity and uncertainty, comfortable with the idea that most experiments will not succeed; also, designing good experiments is a crucial part of the R& D process. - Skilled at analyzing problems from multiple angles and generating a high volume of potential solutions. Preferred Qualifications : - Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (Tier 1 colleges are preferred) - Minimum of 3 years of hands-on experience in data analysis, modeling, and AI solutions development If you're passionate about leveraging data to drive business decisions and have a track record of delivering impactful AI solutions, we want to hear from you! Mode of Work : On-Site (ref:hirist.tech)

Location: bangalore, IN

Posted Date: 5/10/2025