Data Scientist Role -

Individual Contributor role only Considered for this Role

- 5 to 8 years of hands-on experience in Data Science, Machine Learning, Predictive Analytics
- Robust proficiency in Python, including experience with data manipulation, statistical analysis, machine learning, and model development using

libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch and related frameworks.
- Solid understanding of statistics, probability theory, hypothesis testing, regression analysis, sampling techniques, and experimental design to support data-

driven decision making.
- Apply statistical and machine learning techniques to analyze large datasets, identify patterns, build predictive models, and generate actionable

business insights.
- Experience in building REST APIs and integrating AI models into production environments.
- Strong understanding of statistics, machine learning algorithms, forecasting techniques, and optimization methods.
- Excellent analytical, problem-solving, and communication skills with the ability to work in cross-functional teams.

Good to have
- Experience with Generative AI technologies, Large Language Models (LLMs)
- Experience working with SQL and NoSQL databases, data warehouses, and big data technologies.
- Familiarity with cloud platforms such as AWS, and containerization technologies such as Docker and Kubernetes.

Roles & Responsibilities
- Collaborate with business stakeholders, product managers, and engineering teams to translate business requirements into analytical solutions.
- Extract and integrate data from multiple sources through APIs, databases, and file-based interfaces.
- Analyze structured and unstructured data to identify trends, patterns, and actionable business insights.




- Perform data preprocessing, feature engineering, model development, deployment and model evaluation
- Evaluate, fine-tune, and optimize AI/ML models to improve accuracy, performance, scalability, and reliability.
- Develop APIs and services for model deployment and integration with enterprise systems.
- Ensure data quality, governance, security, and compliance throughout the analytics lifecycle.
- Stay current with emerging AI, GenAI, machine learning, and data science technologies and recommend their adoption where appropriate.

LeaD AI Engineer

- Python (Mandatory)
- JavaScript/TypeScript (Preferred)
- Database [Vector DB & Redis]

Backend Development
- FastAPI
- Django
- REST APIs
- WebSockets
- Async Programming (asyncio)
- Microservices
- Redis

1. Large Language Models (LLMs)

Must have experience with:
- OpenAI APIs (Chat Completions / Responses API)
- GPT-4o / GPT-5 or equivalent LLMs
- Claude
- Gemini (Preferred)

Good understanding of:
- Prompt Engineering
- Function Calling / Tool Calling
- Structured Outputs
- JSON Schema
- Context Window Management
- Token Optimization
- AI Safety
- Model Evaluation

1. Voice AI

Hands-on experience with:
- Speech-to-Text (STT)
- Text-to-Speech (TTS)
- OpenAI Realtime API
- Streaming Audio
- Voice Activity Detection (VAD)
- Realtime WebSocket APIs

1. Retrieval-Augmented Generation (RAG)

Experience with:
- Embeddings




- Vector Databases

Preferred databases:
- Redis Vector Search
- Pinecone
- Weaviate
- Qdrant
- Milvus

AI Libraries & Frameworks

Strong experience with

- OpenAI SDK
- LangChain
- LlamaIndex
- Hugging Face Transformers
- Sentence Transformers
- Pydantic AI

Preferred Domain Experience
- Conversational AI
- Voice AI
- AI Assistants
- Customer Support Automation
- Workflow Automation

Good to have
- MCP (Model Context Protocol)
- AI Guardrails
- Prompt Versioning
- Cost Optimization
- AI Evaluation Frameworks

Roles & Responsibilities
- Design and develop AI-powered enterprise applications using LLMs.
- Build Voice AI solutions for real-time conversational systems.
- Develop AI Agents capable of reasoning, planning, and tool execution.
- Design and implement RAG pipelines using vector databases.
- Integrate AI services with REST APIs, WebSockets, SIP, and enterprise systems.
- Develop scalable Python microservices.
- Optimize AI applications for latency, cost, and accuracy.
- Build reusable AI workflows and tool-calling frameworks.
- Collaborate with Product, QA, and DevOps teams.
- Evaluate and integrate emerging AI technologie

Pay: ₹1,041,746.90 - ₹2,500,000.00 per year

Benefits

- Health insurance
- Provident Fund

Application Question(s):
- What is your current location?
- What is your current ctcc?
- What is your salary expectation?
- What is your notice period ?
- Mention your technical skills
- We have only f2f round of interview procedure are you comfortable to go ( Yes/No)?

Experience:
- Total : 5 years (Preferred)
- Data, Scientist: 5 years (Preferred)
- AI Engeenering: 7 years (Preferred)

Work Location: In person

📌 Senior AI Enginner / Senior AIML Data Scientist (Hyderabad)
🏢 Vertex Cosmos Solutions
📍 Hyderabad