Key Responsibilities

AI / ML Development

- Design, develop, test, and deploy AI/ML and Generative AI solutions aligned with project requirements.
- Implement LLM‑based solutions using prompt engineering, RAG (Retrieval Augmented Generation), embeddings, and model orchestration.
- Develop and optimize ML models for prediction, classification, NLP, or computer vision use cases.
- Fine‑tune models and improve accuracy, performance, and cost efficiency.

Application & Integration

- Integrate AI components with enterprise applications, APIs, and data pipelines.
- Develop REST APIs or microservices to expose AI capabilities.
- Work with structured and unstructured data from multiple sources.

Cloud & Platforms

- Build and deploy AI solutions on Azure / AWS / GCP (project‑specific).
- Work with platforms such as Azure OpenAI, Azure ML, AWS SageMaker, Vertex AI, or equivalent.
- Support CI/CD pipelines and containerized deployments (Docker/Kubernetes where applicable).

Project Delivery

- Own assigned modules and deliver as per SOW, timelines, and quality standards.
- Participate in Agile ceremonies (sprint planning, stand‑ups, reviews).
- Provide estimates, impact analysis, and technical inputs during solutioning.

Quality, Security & Compliance

- Ensure adherence to secure coding, data privacy, and AI governance guidelines.
- Perform unit testing, debugging, and documentation.
- Support production issues,



enhancements, and model retraining when required.

Collaboration & Communication

- Collaborate with Data Scientists, Architects, PMs, and business stakeholders.
- Clearly explain AI concepts and solution behavior to non‑technical audiences.
- Mentor junior team members (B1/B2) when required.

Required Skills & Experience

Technical Skills

- Strong programming skills in Python (mandatory).
- Hands‑on experience with ML frameworks: TensorFlow, PyTorch, scikit‑learn.
- Experience with Generative AI / LLMs (OpenAI, Azure OpenAI, HuggingFace, etc.).
- Knowledge of prompt engineering, embeddings, vector databases.
- Experience with SQL/NoSQL databases.
- API development experience (REST, JSON).

Cloud & DevOps

- Experience with at least one cloud platform: Azure / AWS / GCP.
- Basic understanding of CI/CD, Git, Docker.
- Familiarity with monitoring, logging, and performance tuning.

Data & AI Concepts

- Robust understanding of ML lifecycle, feature engineering, evaluation metrics.
- Knowledge of NLP concepts is highly desirable.
- Awareness of AI ethics, bias, and responsible AI principles.

Experience & Qualification

- 5–8 years of overall IT experience.
- 2+ years of hands‑on experience in AI/ML or Generative AI projects.
- Bachelor's degree in Engineering, Computer Science, or equivalent.

📌 Aiml (India)
🏢 TalentOla
📍 India