Machine Learning jobs in India

In this role, you will lead the innovation and support of our dynamic pricing program, directly impacting growth, profitability, and overall efficiency.

Work with cross-functional & cross-regional teams for data analysis, monitoring and forecasting, creating the logic for and implementing strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience.

The Data Scientist contributes to build innovative scenarios to understand and anticipate future business or operational value creation levers for the company.

Build the AI capability from scratch.

Work with the Founder for the strategic decisions for the organisation.

Build the AI capability from scratch.

Work with the Chief AI Officer for the strategic decisions for the organisation.

Setup the CoE for AI and work on development of AI architecture basis researc and research.

The Director (AI) will lead the Artificial Intelligence team, shaping the company's vision for AI integration within Mixed Reality (MR) experiences. He/She will be responsible for building a high-performing team, defining the AI strategy, and driving the development and implementation of AI solutions across its product portfolio.

The ideal candidate will drive AI vision and strategy, while also diving deep into the realm of real-time
sports analytics.

To design, develop, implement AI algorithms in an embedded/cloud environment

• Define and manage execution of the Research Group's business strategy including target definitions, growth areas and business plans.

You will build and mentor a team of data scientists and machine learning engineers, collaborating closely with cross-functional teams to integrate AI models and analytics tools into our ecosystem. This role involves driving innovation in how we use AI and machine learning to automate and optimize the organisation's strategies.

Leadership role in overseeing the company's analytics function. This individual will be responsible for developing and executing the data strategy, utilising advanced analytics and machine learning techniques to derive actionable insights that drive key business decisions and enhance product offerings. The role demands a combination of strategic thinking, technical expertise, and the ability to guide teams in leveraging data

This role needs specializing in machine learning or a related field having 4+ years' experience in supporting development of production-ready solutions leveraging AI technologies: NLP, Deep Learning, Machine Learning Responsibilities

• Develop predictive models using supervised and unsupervised machine learning/deep learning
• Build models for legal predictive analytics, natural language understanding, conversational AI, robotic accounting, forecasting and anomaly detection
• Provide expertise in data wrangling, exploratory data analysis and feature engineering with large data sets
• Support the development of proofs of concept to demonstrate the application of AI/ML capabilities in solving customer problems in collaboration with product and other development teams
• A self-starter who can align the technology solution with a business goal Qualifications
• 3+ years' experience in supporting development of production-ready solutions leveraging AI technologies: NLP, Deep Learning, Machine Learning
• Strong hands-on expertise in Python and open source libraries/frameworks/tools such as NumPy, SciPy, scikit-learn, pandas, matplotlib, spaCy, NLTK, jupyter, anaconda, transformers, etc.
• Experience with deep learning frameworks such as TensorFlow, Keras, PyTorch
• Experience in applying deep learning to NLP
• Computer vision modeling a plus
• Experience with designing, building, and optimizing data and model training pipelines
• Experience in SageMaker or Azure ML Studio a plus
• Experience with cloud-based platforms (AWS or Azure) for solution delivery
• Experience working with agile and Software Development Lifecycle tools (e.g. JIRA, Confluence, Git) and Test-Driven Development (TDD)