Senior Machine Learning Engineer
Location
Bangalore | India
Job description
Kindly please read carefully the Roles & Responsiblities and if you are good enough for this position then apply.
- Company - Porter
- Business Unit - Product Experience - Data & Analytics
- Department - Decision Systems - Machine Learning
- Experience - 4 - 7 Years
- Employee Type - Permanent
- Location - Head Office, Bengaluru, Karnataka , India (WC_002)
- Remote Job - No
Data Ambitions @ Porter
Porter collects data at scale about how our customers, our drivers, and our teams make decisions on every transaction every day. Using the insights embedded in this data, we can make better decisions about everything — from the markets we target to the products we deliver in them, to significantly outperforming conventional processes.
We deliver on data-led innovations to put this data to work and capitalise it as a strategically important asset.
Responsibilities
- Work closely with MLEs, MLOps, Data Engineers, and Data Scientists to build and extend our DS/ML platform and use cases.
- Build MVP applications to showcase the value of DS/ML models, owning the end-to-end process.
- Develop re-usable production-grade functionality and automation around DS/ML feature pipelines, real-time/batch inference, continuous training, model monitoring, and more.
- Participate in design sessions and brainstorming with the team on how to solve complex data problems with scalable solutions.
- Work closely with Data Scientists to support productionizing their use case.
- Use Python, Spark, AWS, Snowflake.
- Perform code review and end-to-end testing.
- Can demonstrate awareness of data visualisation tooling and techniques.
Ideal Candidate will
- Decent understanding of Machine Learning Systems (model training, model inference, APIs, feature pipelines, continuous training, model monitoring).
- Have 5 to 8 years of experience as data scientist, data analyst with an appropriate background in ML, DL or statistical modeling.
- Have experience and awareness of applying popular analytical and statistical techniques.
- Have knowledge of serving a model and its pipelines in production.
- Be familiar with a machine learning framework : PyTorch (preferred), TensorFlow, or Keras.
- Understand concepts of linear algebra and/or statistics where applicable.
- Understand the patterns, anti-patterns, pitfalls of all important techniques outlined in the Responsibilities.
- Good proficiency in the language of their choice. ( Matlab doesn't count ???? ).
- Have excellent communication skills and can work in a team.
Kindly please Read carefully the Roles & Responsiblities and then apply.
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