4 - 8 years

9 - 13 Lacs

Posted:4 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

We are looking for a Machine Learning Engineer / Data Scientist to drive the improvement, evaluation, and optimization of our AI solutions. This role will focus on model development, fine-tuning, and evaluation, ensuring our AI applications and intelligent agents perform at the highest levels of accuracy, efficiency, and reliability.

You will collaborate closely with AI Developers to integrate your optimized models into production systems. Work closely with business stakeholders to define meaningful success metrics. The role blends hands-on engineering with data science experimentation, making it ideal for someone passionate about improving real-world AI solutions.

Responsibilities:

  • Fine-tune, optimize, and retrain ML/AI models.
  • Build and maintain evaluation pipelines to test accuracy, robustness, fairness, and efficiency.
  • Automate ML workflows and lifecycle management.
  • Access and prepare high-quality datasets for training and evaluation.
  • Perform light feature engineering and data transformations needed for model optimization.
  • Implement monitoring and feedback loops to track model performance post-deployment.
  • Conduct benchmarking and A/B testing to validate model improvements.
  • Work with Databricks Mosaic AI and cloud ML services (Azure ML, AWS SageMaker) for scalable workloads.

Required Skills and Experience:

  • Experience (4 to 8 Years), Proven background in machine learning engineering and MLOps practices.
  • Proficiency in Python with ML/AI frameworks such as PyTorch, TensorFlow, scikit-learn.
  • Hands-on experience with MLflow for model tracking, deployment, and lifecycle management.
  • Experience fine-tuning LLMs or training traditional ML models.
  • Familiarity with evaluation frameworks (DeepEval, RAGAS, custom pipelines).
  • Strong SQL skills and ability to work with structured/unstructured datasets.
  • Exposure to Spark/Databricks for data processing.
  • Understanding of Deep Learning and Neural Network architectures.
  • Experience with cloud ML platforms (Azure, AWS).

Nice To Have Skills and Experience:

  • Familiarity with LangChain/LangGraph evaluation and testing tools.
  • Experience with vector databases (Pinecone, FAISS, Weaviate, Chroma).
  • Knowledge of bias, fairness, and explainability tools (SHAP, LIME, InterpretML).
  • Awareness of modern ML benchmarks (HELM, MMLU) for LLM evaluation.

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ARM Embedded Technologies

Technology / Embedded Systems

San Jose

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