Job Location: Bangalore/Bengaluru
As a Machine Learning Architect, you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. As MLOps Architect, you will envision, build, deploy and operationalize an end-to-end machine learning (ML) and AI pipeline. You will collaborate with business partners and domain experts to design and develop innovative solutions with the models to achieve predefined outcomes.
The Ideal candidate will
- Engage with clients to understand current and future business goals and translate business problems into high level solution approach.
- Interpret real-time analysis of data to automate and increase efficiency across all business domains, setting the stage for meaningful AI that moves from reactive to predictive.
- Help build a robust enterprisewide architecture for AI/ML and collaborate with data scientists, data engineers, developers, operations and security.
- Work hands-on on designing and building the model deployment based on in-depth understanding of underlying data, data structures, and business problems to ensure deliverables meet client needs.
- Effectively communicate the approach and insights to a larger business audience.
- Guide team members and collaborate with peers and leadership at Tredence and client companies.
Roles Responsibilities
- Work with world biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
- Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
- Work in a diverse environment that keeps evolving
- Hone your entrepreneurial skills as you contribute to growth of the organization
Qualification Experience
- BE/B. Tech/M. Tech
- 6 years of hands-on experience building the end-to-end design, development, and deployment of predictive modelling solutions.
- 3 years of experience in Python/R, SQL
- 3 years of experience in NLP algorithms, Regression Classification Modelling, Time Series Forecasting
- 4 hands on work experience in DevOps
- MLOPs skills like Feature Store, mlflow, model registry, microservices architecture, Flask, Docker, Kubernetes – Combination of these skills
- Exposure on Azure cloud technologies like Databricks, Azure, Azure ML, Azure Monitor
- Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
- Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
- Experience with one or more Container-ecosystem (Docker, Kubernetes)
- Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
- Good understanding of OOP Data Structures concepts
- Proficient in Shell Scripting and automation tools
- Team leading experience of at least 3 year, client interaction and engagement leading, identifying future opportunities for client retention
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