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ML Engineer

Experience: 5+ Years
Location : Hyderabad

About the Role:

We are seeking a highly skilled and experienced Machine Learning Engineer to lead the design and implementation of cutting-edge ML solutions across our organization.  You will be responsible for prototyping and taking models all the way from proof-of-concept to production deployment. This role requires a deep understanding of ML algorithms, data processing pipelines, model optimization, and production-grade engineering practices.


Key Responsibilities:

  • Build and validate ML prototypes to solve real business problems
  • Develop, test, and optimize ML models using structured and unstructured data
  • Design and implement scalable data pipelines and model serving infrastructure
  • Continuously monitor, improve, and re-train models in production
  • Ensure reproducibility, versioning, and documentation of models and experiments
  • 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.
  • 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.
  • 5+ years of professional experience with at least 3 years in machine learning and data science.
  • Take at least one ML solution from idea to full-scale production deployment
  • 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 any of 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.

Preferred Qualifications:

Contributions to open-source ML projects or research publications.

Experience with deep learning, NLP, computer vision, or reinforcement learning.

Familiarity with data privacy, AI ethics, and governance frameworks.

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