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AI / ML Engineer

AI / ML Engineer

Bright & Smart HR SolutionsIndia
6 hours ago
Job description

AI / ML Engineer  – 3 to 5 yrs

6 to 8 yrs

NP : Immediate to 1 week (official) |  Location :  Gurgaon

Job Description – AI / ML Engineer

We are seeking a highly skilled  AI / ML Engineer  with strong expertise in  Python programming, API development, and real-time deployment of ML models . The ideal candidate should have experience in designing, building, and optimizing machine learning pipelines and integrating models into production environments. Key Responsibilities

  • Design, develop, and optimize  machine learning models  using Python and popular ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
  • Implement  end-to-end ML pipelines  including data pre-processing, feature engineering, training, evaluation, and deployment.
  • Build and manage  RESTful APIs / gRPC services  to expose ML models for real-time inference.
  • Deploy and scale models in  production environments  (Docker, Kubernetes, cloud platforms such as AWS, GCP, or Azure).
  • Ensure  high availability, low-latency, and fault-tolerant  real-time ML systems.
  • Collaborate with data engineers and software teams to integrate ML solutions into existing applications.
  • Conduct  performance monitoring, optimization, and retraining  of models as needed.
  • Apply  MLOps best practices  for CI / CD pipelines, model versioning, and automated deployment workflows.
  • Write clean, efficient, and  production-grade Python code  following software engineering best practices.

Required Skills & Experience

  • 3-8 years  of hands-on experience in  Python programming  (advanced knowledge of data structures, OOP, multiprocessing, async programming).
  • Strong expertise in  machine learning algorithms , model training, and evaluation techniques.
  • Experience with  API development  (FastAPI, Flask, Django, or similar).
  • Proven experience in  real-time model deployment  and serving (TensorFlow Serving, TorchServe, MLflow, or custom solutions).
  • Solid understanding of  cloud-native deployments  (AWS Sagemaker, GCP Vertex AI, Azure ML) and containerization (Docker, Kubernetes).
  • Knowledge of  streaming data frameworks  (Kafka, Spark Streaming, Flink) is a plus.
  • Familiarity with  CI / CD pipelines  for ML (GitHub Actions, Jenkins, or similar).
  • Strong grasp of  data engineering concepts  (data ingestion, transformation, and storage).
  • Experience in  monitoring & logging  (Prometheus, Grafana, ELK, or equivalent).
  • Nice to Have

  • Experience with  Generative AI (LLMs, diffusion models, transformers) .
  • Exposure to  GPU optimization and distributed training .
  • Familiarity with  feature stores  and advanced  MLOps frameworks  (Kubeflow, TFX, MLflow).
  • Note : AI / ML engineer

    Python heavy

    Live project hands on experience with deployment

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    Engineer • India

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