Job Description

More like ML Engineer with Python, ML techniques like Timeseries, Regression, Clustering, Classification, SQL

Pluto7 is a forward thinking, Google Cloud Premier Partner, ranked by Google as one of the Top Partners with focus on Supply Chain, ML, Ai, Data Analytics services on Google Cloud Platform (GCP). Pluto7 is a tech-enabled solutions and services company that ignites digital transformation providing supply chain solutions across industries such as Retail, Manufacturing, Hitech, Healthcare and Automobile using AI/ML helping customers enable various Data Management processes and Smart Analytics frameworks to unify their data and move it to the cloud so that it’s ready for AI and ML applications. Pluto7 solves global-scale problems leveraging Smart Analytics in a simplistic way and Pluto7 services and AI solutions deliver innovation and intelligence to build a data-driven future allowing businesses to speed up and scale-out sophisticated machine learning models. Pluto7 has successfully guided many businesses through the digital transformation process by leveraging the power of Google Cloud. In an age where innovation is happening all around us, Pluto7 is on a mission to build a culture where employees are constantly learning, growing and innovating while solving global scale problems leveraging advanced technologies in a simplistic manner. We are a small but extremely impactful team, passionate about GCP and who love experimenting with new technologies creating innovative solutions. We are really excited to find people who have similar passions and are eager to innovate and solve customer problems. We closely partner with Google Industry solutions, Google Engineering and various Google Cloud organizations

Role: Principal Architect - Applied Machine Learning
Experience: 10+ years
Work location: India
The ideal candidate will have a strong knowledge of ML, NLP, Deep Learning, Knowledge Graphs and have experience working with massive amounts of data. They should also have strong software engineering skills and the ability to build systems that reach Entperise scale.
What You'll Do:

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  Build and train production-grade ML models on large-scale datasets to solve various business use cases for Supply Chain.
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  Use large-scale data processing frameworks for feature engineering and be proficient across various data both structured and un-structured.
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  Use Deep Learning models like CNN, RNN and NLP (BERT) for solving various business use cases like name entity resolution, forecasting and anomaly detection.
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  Ability to build ML models across Public and Private clouds including container-based Kubernetes environments.
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  Develop end-to-end ML pipelines necessary to transform existing applications and business processes into true AI systems.
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  Build both batch and real-time model prediction pipelines with existing application and front-end integrations.
• You will collaborate to develop large-scale data modeling experiments, evaluating against strong baselines, and extracting key statistical insights and/or cause and effect relations.

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  Advanced Degree in field of Computer Science, Data Science or equivalent discipline.
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  Minimum 5+ years of working experience as a data scientist
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  Expertise with Python, PySpark, DL frameworks like TensorFlow and MLOps.
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  Experience in designing and building highly scalable distributed ML models in production (Scala, applied machine learning, proficient in statistical methods, algorithms)
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  Experience with analytics (ex: SQL, Presto, Spark, Python, AWS suite). Awareness of the same in GCP would be a plus.
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  Experience with machine learning techniques and advanced analytics (e.g. regression, classification, clustering, time series, econometrics, causal inference, mathematical optimization)
• Experience working with end-to-end pipelines using frameworks like KubeFlow, TensorFlow and/or crowd-sourced data labeling a plus