Expoint - all jobs in one place

מציאת משרת הייטק בחברות הטובות ביותר מעולם לא הייתה קלה יותר

Limitless High-tech career opportunities - Expoint

Microsoft Data & Applied Scientist II 
India, Telangana, Hyderabad 
452128021

24.09.2024

We would like you to get a peek into our culture on Instagram (

Visit us at

REQUIRED QUALIFICATIONS

  • Master’s/PhD degree in CS/EE or related fields with knowledge in NLP, Machine Learning and Data Mining.
  • 2+ years of hands-on experience with ML/NLP frameworks like PyTorch, Tensorflow, ONNX and HuggingFace.
  • Strong data mining and analysis skills using Big Data platforms like Spark, MapReduce, Hadoop etc.
  • Strong knowledge and skills in machine learning software development and architectures for machine learning (with focus on deep learning)
  • Excellent problem solving and data analysis skills
  • Outstanding communication and collaboration skills.
  • Strong software design and development skills
  • Excited to work as part of diverse team and collaborate across geographies.

PREFERRED QUALIFICATIONS

  • Strong research and/or development experience with machine learning, NLP and data mining.
  • Experience in architecting, developing, and delivering advanced NLP projects is a strong plus.
  • Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action.
  • Proven track record on shipping products/services with high quality.
Responsibilities

Your responsibilities include:

  • Developing novel machine learning and data mining algorithms,
  • Designing and developing solutions that respond in real time,
  • Build data quality checks and re-usable modules for the training,
  • Host ML models with production-ready code and integrating them with production pipelines
  • Designing and executing offline/online experiments,
  • Advancing the state of the art of NLP technologies for real world scenarios,
  • Investigating and solving NLP accuracy and robustness issues across all processing chains, including model development, test and quality control, deployment, and user feedback stages.
  • Evaluating product impact via controlled statistical experiments and iterating on technique to deliver maximum business impact