ML Architect

2 weeks ago

Hyderabad, Telangana, India AAGATIServe Full time ₹ 20,00,000 - ₹ 25,00,000 per year

About the Role:

We are seeking a highly skilled and experienced 
Machine Learning Engineer Architect
 to lead the design and implementation of cutting-edge ML solutions across our organization. You will be responsible for driving the end-to-end architecture of ML systems, from data ingestion and model development to deployment and monitoring. This is a leadership role that requires strong technical expertise, strategic thinking, and the ability to collaborate across teams.

Responsibilities

  • Design and lead the architecture of scalable and reliable ML systems and pipelines.
  • Collaborate with data engineers to implement ML models in production environments.
  • Evaluate and select appropriate ML tools, frameworks, and technologies to meet business requirements.
  • Oversee the full ML lifecycle including data preparation, model development, training, validation, deployment, and monitoring.
  • Ensure adherence to MLOps best practices and governance (CI/CD for ML, versioning, reproducibility).
  • Define and implement architecture standards, patterns, and frameworks for machine learning systems.
  • Lead performance tuning, scalability, and optimization efforts.
  • Stay up to date with the latest advancements in AI/ML technologies and propose innovative solutions.
  • Collaborate with stakeholders to translate business needs into ML solutions.

Required Skills & Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field.
  • 10+ years of professional experience with at least 5 years in machine learning and data science.
  • Strong programming skills in 
    Python
    , with experience in ML libraries like 
    TensorFlow, PyTorch, Scikit-learn, XGBoost
    , etc.
  • Deep understanding of 
    ML architecture patterns
    , 
    data pipelines
    , and 
    distributed systems
    .
  • Experience with cloud platforms like 
    AWS, Azure, or GCP
     and cloud-native ML tools (SageMaker, Vertex AI, Azure ML).
  • Proficiency in 
    Docker
    , 
    Kubernetes
    , and other containerization/orchestration tools.
  • Strong grasp of 
    MLOps
    , 
    model monitoring
    , and 
    continuous integration/deployment
     pipelines.
  • Hands-on experience with big data technologies like 
    Spark, Hadoop, Hive
    , or similar.
  • Excellent communication, leadership, and problem-solving skills.

Preferred Qualifications:

  • Experience with 
    deep learning
    , 
    NLP
    , 
    computer vision
    , or 
    reinforcement learning
    .
  • Familiarity with 
    data privacy
    , 
    AI ethics
    , and 
    governance
     frameworks.
  • Contributions to open-source ML projects or research publications.

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