Machine Learning Engineer

13 hours ago


Bengaluru, Karnataka, India EarnIn Full time ₹ 6,00,000 - ₹ 18,00,000 per year

POSITION SUMMARY

As a Fintech company where Machine Learning (ML) is one of the key drivers of growth, our operations highly rely on machine learning models, from business decisions to customer experiences. Therefore, building and deploying state-of-the-art machine learning systems to drive impact via our data capabilities is key. To guarantee the success of machine learning systems, we need to conduct detailed formulation, extensive experimentation, and transform ML models into high-performance, production-level code, including implementing sophisticated machine learning algorithms, robustness monitoring, and system logging and alarming. To support this effort, we are seeking an entry-level Machine Learning Engineer.

This position will be hybrid from our Bengaluru office as part of our expanding site location (2 days a week in the office). EarnIn provides excellent employee benefits, including healthcare, internet/cell phone reimbursement, a learning and development stipend, and opportunities to collaborate with and travel to our Palo Alto HQ and Bangkok Site. Our salary ranges are determined by role, level, and location.

WHAT YOU'LL DO

  • Collaborate closely with other machine learning engineers and analysts to use and train state-of-the-art ML models for the product use cases assigned.

  • Understand the key metrics needed for such model evaluations

  • Do in-depth data analysis to uncover insights and share them with the partner

  • Help in ensuring improvements in our current ML systems via model, data, or experimentation upgrades

  • Gain hands-on experience with various technologies, including PyTorch, AWS, Kafka, data bricks, etc.

WHAT WE'RE LOOKING FOR

  • 1 years of experience working in machine learning systems and an eagerness to create impact

  • Bachelor's, master's, or PhD in Computer Science, Information Technology, or a related field, or related equivalent experience

  • Demonstrate a keen interest in machine learning systems and eagerness to create impact via state-of-the-art data capabilities.

  • Strong understanding of statistical models, familiarity, and in-depth understanding of machine learning and deep learning algorithms, such as clustering and classification.

  • Proficient in at least one programming language, with a familiarity with basic data structures and algorithms.

  • Having experience with big data and familiarity with distributed computation frameworks, such as Hadoop, Spark, and Hive, is desired but not mandatory.

  • Equipped with good verbal and written communication skills.

  • Detail-oriented, with a meticulous approach to problem-solving and project execution

  • Committed to taking ownership of projects, conducting thorough investigations, and driving initiatives to conclusion.

#LI-Hybrid



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