Hiring For Machine Learning Engineer II HyderabadII Work from office

Role: Machine Learning Engineer

Exp: 3-8 years

Notice period: Immediate

Mode: Work from office(5 days)

Location: Hyderabad

Looking for a driven and innovative Machine Learning Engineer to help us scale and foresee problems that aren't apparent.

We're seeking a hands-on individual with a strong passion for data and a proven ability to translate complex data challenges into robust, scalable machine learning solutions. In this role, you'll be a key player in developing, deploying, and maintaining ML models that directly impact our core business functions and enhance user experiences. If you thrive in a collaborative, fast-paced environment, excel at working with diverse data sources, and possess a solid foundation in machine learning principles and MLOps, we encourage you to apply.

Key Responsibilities

• Design, develop, and implement end-to-end machine learning models, from initial data exploration and feature engineering to model deployment and monitoring in production environments.
• Build and optimize data pipelines for both structured and unstructured datasets, focusing on advanced data blending, transformation, and cleansing techniques to ensure data quality and readiness for modeling.
• Create, manage, and query complex databases, leveraging various data storage solutions to efficiently extract, transform, and load data for machine learning workflows.
• Collaborate closely with data scientists, software engineers, and product managers to translate business requirements into effective, scalable, and maintainable ML solutions.
• Implement and maintain robust MLOps practices, including version control, model monitoring, logging, and performance evaluation to ensure model reliability and drive continuous improvement.
• Research and experiment with new machine learning techniques, tools, and technologies to enhance our predictive capabilities and operational efficiency.

Required Skills & Experience

• 3-8

  years of hands-on experience

  in building, training, and deploying machine learning models in a professional, production-oriented setting.
• Demonstrable experience with

  database creation and advanced querying

  (e.g., SQL, NoSQL), with a strong understanding of data warehousing concepts.
• Proven expertise in

  data blending, transformation, and feature engineering

  , adept at integrating and harmonizing both structured (e.g., relational databases, CSVs) and unstructured (e.g., text, logs, images) data.
• Strong practical experience with

  cloud platforms for machine learning development and deployment; significant experience with Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Dataflow) is highly desirable.

• Proficiency in programming languages commonly used in data science (e.g.,

  Python

  is preferred, R).
• Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction) and experience with advanced techniques like

  Deep Learning, Natural Language Processing (NLP), or Computer Vision

  .
• Experience with machine learning libraries and frameworks (e.g.,

  scikit-learn, TensorFlow, PyTorch

  ).
• Familiarity with

  MLOps tools and practices

  , including model versioning, monitoring, A/B testing, and continuous integration/continuous deployment (CI/CD) pipelines.
• Experience with containerization technologies like

  Docker

  and orchestration tools like

  Kubernetes

  for deploying ML models as REST APIs.
• Proficiency with

  version control systems (e.g., Git, GitHub/GitLab)

  for collaborative development.

Educational Background

• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Data Science, or a closely related quantitative field.