Employees in this job function are responsible for designing, building, deploying and scaling complex self-running ML solutions in areas like computer vision, perception, localization etc. They also automate and optimize the end-to-end ML model lifecycle using their expertise in experimental methodologies, statistics, and coding for tool building and analysis.

Key Responsibilities :

- Collaborate with business and technology stakeholders to understand current and future ML requirements

- Design and develop innovative ML models and software algorithms to solve complex business problems in both structured and unstructured environments

- Design, build, maintain and optimize scalable ML pipelines, architecture and infrastructure

- Use machine language and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy

- Adapt machine learning to areas such as virtual reality, augmented reality, object detection, tracking, classification, terrain mapping, and others.

- Train and re-train ML models and systems as required

- Deploy ML models and algorithms into production and run simulations for algorithm development and test various scenarios

- Automate model deployment, training and re-training, leveraging principles of agile methodology, CI/CD/CT (Continuous Integration/ Continuous Deployment/ Continuous Training) and MLOps

- Enable model management for model versioning and traceability to ensure modularity and symmetry across environments and models for ML systems

- Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making

- Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making

- Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends

- Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation

- Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Skills Required :

- Python

- CI-CD

- LLM

- Deep learning

- API

- AI/ML, ALGORITHMS

Skills Preferred : Big Query

Experience Required :

- Practitioner : 1 coding language or framework. 4+ years in IT; 3+ years in development

Experience Preferred :

- CI/CD for ML (GitHub Actions, Jenkins)

- Experience with cloud platforms : AWS/GCP/Azure with AI services (SageMaker, Vertex AI, Bedrocknice to have)

- Problem-Solving & Solution Ownership : Able to identify the right ML approach (fine-tuning, retrieval, prompting, multimodal pipeline).

- Ability to break vague product problems into clear ML tasks. Skilled in PoC building, quick prototyping, and converting them into production systems.

- Capability to estimate feasibility, complexity, cost, and timelines of ML solutions.

- Employees in this job function are responsible for predicting and/ or extracting meaningful trends/ patterns/ recommendations from raw data, leveraging data science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc.