Ai/ml - Solution Architect

1 week ago

India Zensar Technologies Full time

**Role Overview**

**Key Responsibilities**
**Solution Design & Architecture**

Define end-to-end AI/ML solution architectures, including data pipelines, model training, deployment, monitoring, and lifecycle management.

Translate business problems into AI/ML use cases and recommend appropriate algorithms, tools, and frameworks.

Ensure AI/ML solutions are scalable, secure, and aligned with enterprise architecture standards.

**Technical Leadership**

Guide data scientists and engineers in developing and optimizing machine learning models.

Provide best practices for feature engineering, model training, validation, and deployment.

Evaluate and recommend AI/ML platforms, tools, and frameworks.

**Implementation & Delivery**

Work with cross-functional teams to implement ML models into production (batch/real-time inference).

Define CI/CD pipelines for ML (MLOps) to ensure model reproducibility and governance.

Collaborate with DevOps, cloud engineers, and product teams for seamless integration.

**Stakeholder Management**

Partner with business units to identify opportunities where AI/ML can add value.

Present solution architecture, technical choices, and business impact to stakeholders.

Support pre-sales, RFPs, and client discussions by providing AI/ML solution expertise.

**Required Skills & Qualifications**
Bachelor’s/Master’s degree in Computer Science, Data Science, AI/ML, or related field.

8-12 years of IT experience with at least 4-6 years in AI/ML solution design and deployment.

Strong expertise in **machine learning, deep learning, NLP, computer vision, and generative AI**.

Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face).

Proficiency in **Python, R, or Java**, with strong coding and debugging skills.

Solid knowledge of **MLOps practices**(CI/CD pipelines, model monitoring, versioning).

Experience with **cloud platforms**(AWS Sagemaker, Azure ML, Google Vertex AI).

Understanding of data architecture (data lakes, ETL pipelines, APIs, data governance).

Strong problem-solving, communication, and leadership skills.

**Preferred Skills (Good to Have)**
Knowledge of **LLMs (Large Language Models)**and prompt engineering.

Experience in AI ethics, fairness, and responsible AI frameworks.

Exposure to edge AI or IoT-based ML deployments.

Experience in big data tools (Spark, Hadoop, Databricks).

Contributions to open-source AI/ML projects or research publications.

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