Machine Learning Engineer

4 weeks ago

Hyderabad, India Motivity Labs Inc Full time

Machine Learning Engineer

Exp: 5-8 years

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

  • 5+ 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.

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