Senior Applied data scientist/ ML engineer

1 week ago

Hyderabad, India Egen Full time

Roles & Responsibilities:


• The role will focus on building out machine learning solutions for Client content and Ad platform. Primary focus will be on unlocking machine learning opportunities in media supply chain, captioning services, ad conditioning, metadata extraction and building foundational machine learning training and inference pipelines at scale.

• You will lead by example and define the best practices, will set high standards for the entire team and for the rest of the organization. You have a successful track record for ambitious projects across cross-functional teams. You are passionate and results oriented. You strive for technical excellence and are very hands-on. Your co-workers love working with you. You have built respect in your career through concrete accomplishments.

• Build cutting-edge capabilities utilizing machine learning and data science (e.g., large language models, computer vision models, advanced ad & content targeting, etc.)

• Lead design and development of machine learning systems.

• Build end to end ML pipelines to train, deploy and server ML models at scale.

• Leverage industry best practices and tools to continually improve teams' ability to build, operate and maintain products.

• Ensure that technical solutions are in line with established Digital strategy, standards in respect to architecture, security, corporate governance, coding standards, monitoring, logging, unit test, and service enablement.


What to Bring:

 

• experience designing, building machine learning algorithms and systems.

• Proficiency in programming languages such as Java, Golang, Python or Scala.

• Good understanding of Distributed systems, design and architecture.

• Proficiency in operating machine learning solutions at scale, covering the end-to-end ML workflow.

• Experience with Deep Learning,NLP, LLMs, Reinforcement Learning, Causal Inference. good knowledge of ML tools and frameworks (TensorFlow, Keras, pyTorch, scikit-learn, Spark).

• Familiarity with real-world ML systems (configuration, data collection, data verification, feature extraction, resource and process management, analytics, training, serving, validation, experimentation, monitoring).

• Experience with offline experimentation and A/B testing.

• Understanding of batch and streaming data processing techniques.

• Knowledge of AWS or similar cloud platforms.

• PhD or master’s in computer science or related discipline.

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