AIML Data Scientist

Role Overview

We are seeking an experienced AIML Data Scientist to tackle business challenges by leveraging Machine Learning and Deep Learning methodologies. This role involves collaborating with cross-functional teams to deliver impactful AI solutions across various domains, using a consultative and hands-on approach.

Key Responsibilities

• Apply and blend multiple AI/ML algorithms to address complex business problems effectively.
• Enhance model accuracy to achieve significant business benefits and accurately estimate the impact of deployed models.
• Engage closely with domain teams to interpret business contexts and data schemas, devising appropriate Deep Learning solutions accordingly.
• Handle data preprocessing and feature engineering with tools such as Python, R, SQL, and cloud-based data pipelines.
• Design, develop, and deploy deep learning models using frameworks like TensorFlow and PyTorch, including processing text, speech, image, and video data.
• Construct and optimize NLP models for tasks such as text classification, entity recognition, relationship extraction, text summarization, topic modeling, semantic search, and reasoning over knowledge graphs using libraries like SpaCy and open-source tools.
• Develop image recognition and video analysis solutions leveraging OpenCV and other open-source platforms.
• Utilize state-of-the-art deep learning techniques and optimize models to achieve maximum accuracy.
• Leverage visualization tools such as Power BI or Tableau to analyze results, validate models, and communicate findings.
• Collaborate with application teams to deploy models either on cloud platforms or on-premises infrastructures, including establishing CI/CD pipelines for streamlined model deployment.
• Integrate AI/ML models with external applications through REST APIs and other connector technologies.
• Maintain continuous learning by keeping up-to-date on latest techniques and best practices, documenting work via white papers and creating demonstrable assets highlighting project impacts.

Technical Expertise

• Strong foundation in machine learning, mathematics, and statistics.
• Experience using version control systems like Git and Github for collaborative development.
• Good comprehension of AI solution landscapes, including cloud services, GPU computation, data security, API gateways, microservices, and big data ingestion, storage, and processing.
• Knowledge of CUDA programming and ability to scale prototype ideas into production-grade solutions.
• Capability to measure and project model impact effectively.

Soft Skills

• Innovative and curious mindset aimed at pioneering new approaches.
• Ability to clearly convey and advocate ideas and processes across different teams and levels of the organization.
• Forward-thinking problem solver who anticipates challenges and plans accordingly.
• Strong communication skills for presenting ideas in large forums.

Preferred Experience

• Active engagement with open source platforms and Kaggle competitions.
• Handling large data processing with tools such as PySpark and Hadoop.
• Exposure to reinforcement learning and optimization/genetic algorithms.
• Hands-on experience operationalizing deep learning models in customer environments, including scalability considerations.
• Familiarity with streaming data processing, robotic process automation (RPA), edge computing, augmented/virtual reality technologies.
• Understanding of digital ethics and data privacy principles.
• Experience with AI and cognitive services platforms like Azure ML, IBM Watson, AWS SageMaker, and Google Cloud is highly desirable.
• Familiarity with platforms like DataRobot, CognitiveScale, and H2O.ai adds value.

Additional Information

• Location: Pan India
• Experience Required: 6 to 15 years
• Notice Period: Immediate up to 90 days
• Interview Mode: In-person