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Machine Learning Solutions Engineer | Bengaluru | 6+ Yrs

  • Zyoin Group
  • India, B...
  • 6 - 8 Yrs

Job Description

  • We are seeking a talented and creative Machine Learning Solutions Engineer to join our growing team. In this role, you will play a critical role in bridging the gap between business needs and cutting edge machine learning solutions within the automotive industry.
  • You will collaborate closely with application and product teams to define, develop, and implement ML solutions that solve real-world business problems.
  • Master's degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience).
  • Minimum 3-5 years of experience in applying machine learning techniques to solve real-world problems.
  • Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning).
  • Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages (Python).
  • Experience with data preprocessing, feature engineering, and model evaluation techniques.
  • Solid understanding of statistical concepts and data analysis methods.
  • Experience building and deploying production-ready machine learning systems (a plus).
  • Experience working within the automotive industry (a plus).
  • Excellent communication and collaboration skills to effectively interact with both technical and non-technical stakeholders.
  • Strong problem-solving and analytical skills with a data-driven approach to decision making.
  • Ability to work independently and manage multiple projects simultaneously.

Job Responsibilities

  • Partner with application and product teams to understand business challenges and opportunities.
  • Translate business requirements into technical specifications for machine learning solutions.
  • Design, develop, and implement machine learning models tailored to solve specific automotive industry problems.
  • Define appropriate evaluation metrics for both offline model training and online model performance monitoring.
  • Continuously monitor and improve model accuracy and performance through data analysis and feature engineering.
  • Integrate diverse data sources into machine learning pipelines to enhance model effectiveness.
  • Develop creative methodologies and approaches to optimize model performance.
  • Design and build production-ready ML systems that integrate with existing applications and support real-time decision making.
  • Communicate effectively with both technical and non-technical stakeholders, explaining complex ML concepts and business impacts.
  • Stay up-to-date on the latest advancements in machine learning research and best practices.


Bengaluru, Karnataka, India