AI Ml Engineer

Position Title:

Department:

Reports To:

Work Location:

Position Summary:

AI/ML Engineer

Essential Duties and Responsibilities:

• Develop, train, and deploy deep learning models using

  PyTorch

  and

  TensorFlow

  .
• Build and optimize

  Computer Vision

  models for:

• Face detection

• Object tracking and recognition

• OCR (Optical Character Recognition)

• ID Verification

• Design and deploy RESTful APIs using

  FastAPI

  ,

  Flask

  , or

  Django

  .
• Develop scalable containerized solutions using

  Docker

  , with orchestration via

  Kubernetes (K8s)

  .
• Integrate and query

  SQL

  ,

  NoSQL

  , and

  Vector Databases

  such as

  Weaviate

  or

  Pinecone

  .
• Run and evaluate

  LLMs locally

  using tools such as

  Ollama

  , including model comparisons and performance tuning.
• Work on NLP tasks including:

• Instruction tuning

  ,

  summarization

  ,

  embedding generation

• Prompt engineering

  (few-shot, CoT reasoning)
• Experience with transformer-based models like

  GPT

  ,

  LLaMA

  ,

  BERT

  ,

  Falcon

• Build and maintain

  RAG pipelines

  using frameworks such as

  LangChain

  ,

  LlamaIndex

  , and

  LangGraph

  .
• Collaborate with cross-functional teams to define technical requirements and deliver high-impact AI solutions.
• Stay current with industry trends in LLMs, vector databases, and agentic AI architectures and MCP (Model context protocol).

Qualifications:

Education & Experience:

• Bachelors or masters degree in computer science, Artificial Intelligence, or a related field.
• Minimum of

  3 years

  of hands-on experience in AI/ML development and deployment.
• Demonstrated experience working with

  LLMs

  ,

  computer vision

  , and

  REST APIs

  .

Core Technical Skills:

• Programming:

  Python

• Frameworks & Libraries:

  PyTorch

  ,

  TensorFlow

  ,

  OpenCV

• API Development:

  FastAPI

  ,

  Flask

  ,

  Django

• Proficiency in DSA (Data Structures and Algorithms).
• Containerization & Version Control:

  Docker

  ,

  Git

  ,

  Kubernetes (K8s)

• Databases:

• SQL

  and

  NoSQL

• Vector Databases

  :

  Weaviate

  ,

  Pinecone

Computer Vision Experience:

• Face detection
• Object tracking and recognition
• OCR
• ID Verification

LLMs & NLP:

• Experience using

  Ollama

  for local LLM exploration and evaluation
• Instruction tuning, summarization, embedding generation
• Prompt engineering techniques (few-shot, chain-of-thought reasoning)
• Familiarity with

  GPT

  ,

  LLaMA

  ,

  BERT

  ,

  Falcon

  , and other transformers

Agentic AI & RAG/KAG:

• Building RAG/KAG pipelines using

  LangChain

  ,

  LlamaIndex

  , and

  LangGraph

• Integration with cloud-hosted, local, and API-based LLMs

Language Ability:

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

Mathematical Ability:

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

Reasoning Ability:

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

Computer Skills:

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

Certificates and Licenses:

None required.

Information Security Management (ISM) and Privacy Statement:

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

Position Description Acknowledgement:

I have reviewed this position description and understand my job duties and responsibilities. I confirm my ability to perform the essential functions outlined. I understand that job responsibilities may change according to business needs and will seek clarification as needed. I recognize that performance evaluations and salary adjustments are tied to my ability to meet the roles expectations.

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