Principal Data Scientist Nlp/voice Ai Job in Tvs Motors
Principal Data Scientist Nlp/voice Ai
Tvs Motors
4+ weeks ago
- Bengaluru, Bangalore Urban, Karnataka
- Not Disclosed
- Full-time
- Permanent
Job Summary
a. Build ML/AI models leveraging a strong understanding of Machine Learning
principles including standard algorithms for Regression and Classification,
Deep Learning constructs (RNN, CNN, RBMs, Auto Encoders, GANs) and
AI systems such as Voice to Text, NLP/NLU and Recommender systems
b. Design and build Voice based analytic systems to provide conversational
features and also use such systems for data capture.
c. Use voice analytics to capture buying intent, additional buying
considerations and voice assisted voice search systems
d. Able to understand the determinants of success for a Machine Learning
system, Model accuracy and efficiency, Data requirements, Training and
Test constructs, CI/CD for ML systems
e. Able to build standard ML systems using available ML components provided
by AWS, Azure and GCP.
2) Cloud & Big Data:
a. Work on Cloud Infrastructure(Azure, AWS) to provision data to ML models,
build ML systems on deploy them at scale
b. Build ML systems using Spark libraries such as ML Lib, Spark SQL and be
able to deploy them on clusters/machines, both on Cloud and on-Prem
c. Put in place systems to continuously monitor, evaluate and re-train ML
models in production
3) Build Production level Models @ scale
a. Design and implement the machine learning lifecycle at scale, from building
the data infrastructure to train/test Machine learning models to their
production environments.
b. Management of production ML workflows ensuring automated CI/CD
capabilities are built into the work flow
c. Design and Implement alerts/dashboards to ensure continuous monitoring
of production models effectiveness ( accuracy, latency, performance etc.,)
Job Requirements
1) Ability Work closely with Data Analysts, Data Scientists and Business Analysts
2) Comfortable to work in cross-functional team and collaborate with peers during
the project lifecycle
3) Open to travel based on the project and teams locations.
Qualifications
BE/B.Tech/BS/MS/PhD in Computer Science or a related field from a Premier institute (
Tier 1 IITs, BITS and Top NITs, Ivy League US Schools)
Experience
1) 4 - 8 years of work experience as a Data Scientist with at least 4-5 years designing
and implementing ML platforms for enterprise-grade ML use cases
2) Start-up experience is a plus
Functional Competencies
1) Masters or Ph.D. in computer science, mathematics, or statistics
2) Strong Data Science experience working with Java, Python, and R
3) Experience with standard ML algorithms, deep neural networks, Gaussian
processes, and reinforcement learning
4) A solid understanding of both probability and statistics
5) A firm understanding of mathematics (including the role of algorithm theory in
machine learning and complex algorithms that are needed to help machines learn
and communicate)
6) Strong analytical and problem solving skills
7) Experience working with large amounts of data in a high throughput environment
8) Experience working with cloud platforms ( Azure, AWS, GCP)
9) Experience working with messaging tools like Kafka, Kinesis, Spark Streaming
10)Extensive knowledge of machine learning evaluation metrics and best practices
- Key Responsibilities
a. Build ML/AI models leveraging a strong understanding of Machine Learning
principles including standard algorithms for Regression and Classification,
Deep Learning constructs (RNN, CNN, RBMs, Auto Encoders, GANs) and
AI systems such as Voice to Text, NLP/NLU and Recommender systems
b. Design and build Voice based analytic systems to provide conversational
features and also use such systems for data capture.
c. Use voice analytics to capture buying intent, additional buying
considerations and voice assisted voice search systems
d. Able to understand the determinants of success for a Machine Learning
system, Model accuracy and efficiency, Data requirements, Training and
Test constructs, CI/CD for ML systems
e. Able to build standard ML systems using available ML components provided
by AWS, Azure and GCP.
2) Cloud & Big Data:
a. Work on Cloud Infrastructure(Azure, AWS) to provision data to ML models,
build ML systems on deploy them at scale
b. Build ML systems using Spark libraries such as ML Lib, Spark SQL and be
able to deploy them on clusters/machines, both on Cloud and on-Prem
c. Put in place systems to continuously monitor, evaluate and re-train ML
models in production
3) Build Production level Models @ scale
a. Design and implement the machine learning lifecycle at scale, from building
the data infrastructure to train/test Machine learning models to their
production environments.
b. Management of production ML workflows ensuring automated CI/CD
capabilities are built into the work flow
c. Design and Implement alerts/dashboards to ensure continuous monitoring
of production models effectiveness ( accuracy, latency, performance etc.,)
Job Requirements
1) Ability Work closely with Data Analysts, Data Scientists and Business Analysts
2) Comfortable to work in cross-functional team and collaborate with peers during
the project lifecycle
3) Open to travel based on the project and teams locations.
Qualifications
BE/B.Tech/BS/MS/PhD in Computer Science or a related field from a Premier institute (
Tier 1 IITs, BITS and Top NITs, Ivy League US Schools)
Experience
1) 4 - 8 years of work experience as a Data Scientist with at least 4-5 years designing
and implementing ML platforms for enterprise-grade ML use cases
2) Start-up experience is a plus
Functional Competencies
1) Masters or Ph.D. in computer science, mathematics, or statistics
2) Strong Data Science experience working with Java, Python, and R
3) Experience with standard ML algorithms, deep neural networks, Gaussian
processes, and reinforcement learning
4) A solid understanding of both probability and statistics
5) A firm understanding of mathematics (including the role of algorithm theory in
machine learning and complex algorithms that are needed to help machines learn
and communicate)
6) Strong analytical and problem solving skills
7) Experience working with large amounts of data in a high throughput environment
8) Experience working with cloud platforms ( Azure, AWS, GCP)
9) Experience working with messaging tools like Kafka, Kinesis, Spark Streaming
10)Extensive knowledge of machine learning evaluation metrics and best practices
Experience Required :
4 to 8 Years
Vacancy :
2 - 4 Hires
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