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Machine Learning Engineer

Machine Learning Engineer

BayOne SolutionsTiruchirappalli, IN
30+ days ago
Job description

Responsibilities :

Machine Learning Development & Implementation (40%)

  • Design and implement end-to-end ML pipelines for recommendation systems, search ranking, and classification problems
  • Build and optimize traditional ML models using techniques such as ensemble methods, SVMs, gradient boosting, and neural networks
  • Develop time series forecasting models and ranking algorithms for complex business applications
  • Implement feature engineering pipelines that handle real-world data noise and edge cases
  • Create robust data preprocessing and validation systems that ensure model reliability in production

Production ML Systems & Deployment (25%)

  • Deploy ML models using Docker containerization and REST API frameworks (Flask / FastAPl)
  • Implement model serving solutions on Azure Container Instances with proper monitoring and

    • alerting

  • Build MLOps pipelines using MLflow for experiment tracking and model registry management
  • Design scalable data workflows using Apache Airflow and Azure Data Factory for ETL operations
  • Establish model versioning, rollback strategies, and performance monitoring in production environments

    • Technical Leadership & Collaboration (20%)

  • Serve as a technical sounding board for AI team members on ML architecture and approach decisions
  • Mentor team members on best practices for production ML system design and implementation
  • Communicate complex technical concepts clearly to both technical and non-technical stakeholders
  • Collaborate across AI, web development, and system architecture teams toensure seamless integration
  • Guide strategic decisions on when to use traditional ML versus generative AI approaches

    • Strategic ML Decision Making (15%)

  • Evaluate problems to determine optimal solutions : classical ML, GenAI, or simpler analytical methods
  • Integrate generative AI tools effectively into workflows without over-relying on them
  • Design ML systems that integrate seamlessly with existing web application architectures
  • Provide technical guidance onmodel selection, evaluation metrics, and performance optimization
  • Stay current with ML best practices while maintaining focus on practical, business-driven solutions

    • Required Qualifications

    Education & Experience

  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field
  • 4+ years of hands-on experience building and deploying machine learning systems in production
  • Proven experience working in non-technical business domains (healthcare, finance, retail, HR, etc.)
  • Track record of mentoring technical team members and leading collaborative projects

    • Core Technical Skills

  • Programming Excellence : Expert-level Python proficiency with focus on clean, maintainable, production-ready code
  • Traditional ML Expertise : Deep understanding of classification, regression, ranking, and recommendation algorithms
  • Production ML : Experience with MLOps practices, model deployment, monitoring, and lifecycle management
  • Data Engineering : Proficiency with data pipeline development, ETL processes, and handling messy real-world datasets
  • Cloud Platforms : Hands-on experience with Azure ML Studio, Azure Container Instances, and Azure Data Factory

    • Specialized Experience :

  • Experience building recommendation engines, search ranking systems, or time series forecasting models
  • Background in A / B testing methodologies and measuring business impact of ML initiatives
  • Knowledge of feature stores, model registry systems, and ML experiment tracking
  • Understanding of model interpretability, bias detection, and fairness in ML systems
  • Experience with both structured and unstructured data processing at scale
  • Experience with deep learning frameworks (TensorFlow, PyTorch) for appropriate use cases

    • Preferred Qualifications

  • Knowledge of natural language processing techniques and text classification systems
  • Background in building ML systems for talent acquisition, recruiting, or HR technology
  • Experience with real-time ML inference and low-latency model serving
  • Understanding of distributed computing and large-scale data processing
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    Machine Learning Engineer • Tiruchirappalli, IN