Machine Learning Engineer
Bengaluru (Bangalore), India
1d ago

How often have you read job descriptions and gone I have read this before or the real job description will come out during the interviews, so why bother reading this .

In other instances when job descriptions are actually well-written, ie not just copied and pasted from somewhere and try doing justice to what you d be doing at the job, 2-

4 months of a typical interview cycle make those descriptions obsolete by the time you actually start at the job.Also not unsurprising then : just like you ignore or skim through job descriptions, most recruiters do the same with your resumes look for specific keywords and leave all the assessment for during the interview itself.

Even worse : the human recruiter in some cases is being replaced by an algorithm to automate screening.

You, therefore, will try to put as many keywords in your resume to ensure you get that interview call.Nobody is being ingenuine in this process but the very process is fundamentally broken.

And that is exactly what we want to solve : create an effective matching of work to the worker that is an accurate and real-

time reflection of both ends, thus increasing the actual engagement with the work itself.ResponsibilitiesIn this role, you ll build and implement novel Machine Learning and Deep Learning systems on our platform as well as help build the infrastructure to train and deploy them.

Specifically, you will : - Design and implement the infrastructure required to train models at scale.

  • Work with the data team s infrastructure to build real-time and offline feature databases.
  • Work with the data team to create the infrastructure to build and maintain the datasets from which models are created -
  • Build the model serving systems with which we can deploy our models to production - As we grow, scale the ML system to be able to support more use cases and ML model types.

    Requirements- 1+ years of experience building production-ready ML models and systems.

  • 3+ years of building distributed systems and / or scalable backend systems and the ability to maintain such systems in production.
  • Strong software engineering fundamentals - understanding of data structures and algorithms, O-notation, ability to maintain a test suite and write clear maintainable code.
  • Familiarity with the majority of the following tools : Tensorflow, Numpy, Scipy, SparkML, pandas, scikit-learn.
  • Demonstrated leadership and self-direction and willingness to both teach others and learn new techniques.
  • Experience with big data processing and storage systems : Hadoop, Spark, Hbase, Cassandra etc.
  • Strong programming skills in Python.
  • Intermediate to Advanced knowledge of SQL and ability to wrangle data from many disparate data sources - Technologies we use : MySQL, Python, AWS, Snowflake, R, and Looker, among many others.

    Skills : - Apache Spark, Hadoop, Machine Learning (ML), Data Science, Apache HBase, Apache Cassandra, Python, TensorFlow, NumPy and pandas

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