Staff Machine Learning Engineer

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks.

We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.

As a Fintech company where Machine Learning (ML) is one of the key features, our operations highly rely on machine learning models, from business decisions to customer experiences. Therefore, ensuring our machine learning systems’ health and scalability is critical. To guarantee the success of machine learning systems, work around transforming ML models to high-performance production-level code needs to be done, including not only implementing sophisticated machine learning algorithms but also robustness monitoring, system logging/alarming, and DevOps.

This position will be ideally hybrid from our Bengaluru office as part of our expanding site location. EarnIn provides excellent benefits for our employees including healthcare, internet/cell phone reimbursement, a learning and development stipend, and potential opportunities to travel to our Palo Alto HQ.  Our salary ranges are determined by role, level, and location.

• →Design, build, and launch efficient and reliable machine learning (ML) models to drive business impact
• →Find innovative and cost-effective solutions to key problems, deliver high-quality code
• →Work with product managers/machine learning engineers/performance, and quality engineers to take the product to market
• →Train and validate both deep learning-based and statistical-based models considering use-case, complexity, performance, and robustness
• →Demonstrate end-to-end understanding of applications and develop a deep understanding of the “why” behind our models & systems
• →Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements, and define the scope of the systems needed
• →Work closely with data platform teams to enable robust scalable batch and real-time data pipelines
• →Drive high engineering standards on the team through mentoring and knowledge-sharing
• →Drive engineering best practices around code reviews, automated testing, and monitoring

• • Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
  • 5+ years of industry machine learning experience and excellent software engineering skills.
  • Familiarity with digital marketing concepts and metrics. Prior experience with Marketing Mix Modeling (MMM), predicted Lifetime Value (LTV), incremental Lift estimation, geo lift tests, and causal inference is a big plus.
  • Expertise in the breadth of machine learning and statistical techniques such as tree-based models, deep learning techniques, and A/B testing.
  • Strong programming skills in Python, and familiarity with ML frameworks such as TensorFlow, PyTorch, XGBoost and Scikit-Learn.
  • Hands-on experience with SQL and data manipulation tools.
  • Experience with ML cloud platforms such as AWS Sagemaker, Databricks, or GCP Vertex AI
  • Strong analytical skills to evaluate business impact and performance metrics of ML implementations and drive continuous improvement
  • Strong communication and collaboration skills.
  • Passion for learning and staying updated with the latest machine learning industry trends.