Position Title: AI/ML Engineer

Department: Data Science

Reports To: Technical Lead

Work Location: On-site

Position Summary:

We are seeking an AI/ML Engineer with 3+ years of hands-on experience in Machine Learning, Deep Learning, and Large Language Models (LLMs) to join our Data Science team. The ideal candidate will be proficient in developing, deploying, and evaluating AI/ML models with a strong background in computer vision, RESTful API development, and working with LLMs in local and cloud-hosted environments. This role requires exposure to advanced tools such as LangChain, Ollama, Weaviate, and LlamaIndex, and provides the opportunity to work on real-world applications using Agentic AI, RAG (Retrieval-Augmented Generation) KAG (Knowledge Augmented Generation) and COT (Chain of thought) pipelines.

Essential Duties and Responsibilities:

1. Develop, train, and deploy deep learning models using PyTorch and TensorFlow.
2. Build and optimize Computer Vision models for:
3. Face detection
4. Object tracking and recognition
5. OCR (Optical Character Recognition)
6. ID Verification
7. Design and deploy RESTful APIs using FastAPI, Flask, or Django.
8. Develop scalable containerized solutions using Docker, with orchestration via Kubernetes (K8s).
9. Integrate and query SQL, NoSQL, and Vector Databases such as Weaviate or Pinecone.
10. Run and evaluate LLMs locally using tools such as Ollama, including model comparisons and performance tuning.
11. Work on NLP tasks including:
12. Instruction tuning, summarization, embedding generation
13. Prompt engineering (few-shot, CoT reasoning)
14. Experience with transformer-based models like GPT, LLaMA, BERT, Falcon
15. Build and maintain RAG pipelines using frameworks such as LangChain, LlamaIndex, and LangGraph.
16. Collaborate with cross-functional teams to define technical requirements and deliver high-impact AI solutions.
17. Stay current with industry trends in LLMs, vector databases, and agentic AI architectures and MCP (Model context protocol).

Qualifications:

Education & Experience:

1. Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field.
2. Minimum of 3 years of hands-on experience in AI/ML development and deployment.
3. Demonstrated experience working with LLMs, computer vision, and REST APIs.

Core Technical Skills:

1. Programming: Python
2. Frameworks & Libraries: PyTorch, TensorFlow, OpenCV
3. API Development: FastAPI, Flask, Django
4. Proficiency in DSA (Data Structures and Algorithms).
5. Containerization & Version Control: Docker, Git, Kubernetes (K8s)
6. Databases:
7. SQL and NoSQL
8. Vector Databases: Weaviate, Pinecone

Computer Vision Experience:

1. Face detection
2. Object tracking and recognition
3. OCR
4. ID Verification

LLMs & NLP:

1. Experience using Ollama for local LLM exploration and evaluation
2. Instruction tuning, summarization, embedding generation
3. Prompt engineering techniques (few-shot, chain-of-thought reasoning)
4. Familiarity with GPT, LLaMA, BERT, Falcon, and other transformers

Agentic AI & RAG/KAG:

1. Building RAG/KAG pipelines using LangChain, LlamaIndex, and LangGraph
2. Integration with cloud-hosted, local, and API-based LLMs

Language Ability:

1. Ability to read and interpret technical documentation and write moderately complex reports or procedures.
2. Strong verbal and written communication skills to convey complex technical concepts to non-technical stakeholders.

Mathematical Ability:

1. Proficiency in probability, linear algebra, calculus, and statistics relevant to machine learning model development and evaluation.

Reasoning Ability:

1. Analytical thinker with problem-solving skills to work through technical challenges.
2. Capable of managing competing priorities and adapting to changing project scopes.
3. Detail-oriented and capable of identifying root causes and implementing data-driven solutions.

Computer Skills:

1. High proficiency in AI/ML tools and platforms, including cloud-based solutions, model deployment stacks, and development environments.
2. Comfortable using collaboration tools (Microsoft Office, Google Suite, Git-based version control).

Certificates and Licenses:

None required.

Information Security Management (ISM) and Privacy Statement:

1. Ensure compliance with data privacy regulations and internal data handling policies.
2. Implement appropriate encryption, access control, and audit logging on AI systems.
3. Participate in regular code reviews, vulnerability scans, and privacy assessments.