ML Engineer

Our Client company is into Telecommunications. (SY1)

ML Engineer

Multi Recruit

Company

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ML Engineer

at Our Client company is into Telecommunications. (SY1)

Agency job

via Multi Recruit

4 - 8 yrs

₹21L - ₹23L / yr

Remote, Bengaluru (Bangalore)

Skills

Machine Learning (ML)

Python

Deep Learning

ML Tools

NLP Tools

Unix

Computer Vision

Participate in full machine learning Lifecycle including data collection, cleaning, preprocessing to training models, and deploying them to Production.
Discover data sources, get access to them, ingest them, clean them up, and make them “machine learning ready”.
Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
Partner with data scientists to understand and implement machine learning algorithms.
Support A/B tests, gather data, perform analysis, draw conclusions on the impact of your models.
Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.
Mentor junior team members

Who we have in mind:

Graduate in Computer Science or related field, or equivalent practical experience.
4+ years of experience in software engineering with 2+ years of direct experience in the machine learning field.
Proficiency with SQL, Python, Spark, and basic libraries such as Scikit-learn, NumPy, Pandas.
Familiarity with deep learning frameworks such as TensorFlow or Keras
Experience with Computer Vision (OpenCV), NLP frameworks (NLTK, SpaCY, BERT).
Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
Understand machine learning principles (training, validation, etc.)
Strong hands-on knowledge of data query and data processing tools (i.e. SQL)
Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
Experience deploying highly scalable software supporting millions or more users
Experience building applications on cloud (AWS or Azure)
Experience working in scrum teams with Agile tools like JIRA
Strong oral and written communication skills. Ability to explain complex concepts and technical material to non-technical users

Participate in full machine learning Lifecycle including data collection, cleaning, preprocessing to training models, and deploying them to Production.
Discover data sources, get access to them, ingest them, clean them up, and make them “machine learning ready”.
Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
Partner with data scientists to understand and implement machine learning algorithms.
Support A/B tests, gather data, perform analysis, draw conclusions on the impact of your models.
Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.
Mentor junior team members

Who we have in mind:

Graduate in Computer Science or related field, or equivalent practical experience.
4+ years of experience in software engineering with 2+ years of direct experience in the machine learning field.
Proficiency with SQL, Python, Spark, and basic libraries such as Scikit-learn, NumPy, Pandas.
Familiarity with deep learning frameworks such as TensorFlow or Keras
Experience with Computer Vision (OpenCV), NLP frameworks (NLTK, SpaCY, BERT).
Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
Understand machine learning principles (training, validation, etc.)
Strong hands-on knowledge of data query and data processing tools (i.e. SQL)
Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
Experience deploying highly scalable software supporting millions or more users
Experience building applications on cloud (AWS or Azure)
Experience working in scrum teams with Agile tools like JIRA
Strong oral and written communication skills. Ability to explain complex concepts and technical material to non-technical users

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