Job Description

About the Role

We are seeking a

Lead AI Engineer

to design, build, and scale our next-generation

conversational AI platform

, including intelligent chatbots, natural language interfaces, and machine learning systems. The ideal candidate has deep expertise in

applied machine learning, NLP/LLMs, MLOps

, and hands-on experience leading end-to-end AI product development--from data strategy to deployment.

Data & Governance Experience of Voice to text as well as Voice to Voice like open AI Whisper

Establish data strategy for conversational AI. Manage model versioning, experimentation logs, and performance metrics. Ensure compliance with ethical AI, data privacy, and security requirements.

Required Skills & Experience

6+ years of experience in applied ML/AI or advanced software engineering. Strong expertise in

NLP, LLMs, and conversational AI frameworks

. Proficiency in

Python

, ML libraries (TensorFlow/PyTorch), and NLP packages. Experience with

cloud platforms (AWS/Azure/GCP)

for ML workloads. Hands-on experience deploying ML models into production at scale. Experience with

vector databases (Pinecone, FAISS), retrieval systems, and RAG

. Strong understanding of

MLOps tools

(e.g., Docker, Kubernetes, MLflow). Proven track record leading complex AI initiatives end-to-end.
You will work closely with product, data, and engineering teams to drive technical vision, develop scalable architectures, and deliver high-quality AI solutions that improve customer experience and business performance.

Key ResponsibilitiesAI Strategy & Architecture

Define technical roadmap for conversational AI products. Design scalable ML architectures for LLM-based chatbots and NLP applications. Select appropriate models, frameworks, tools, and cloud infrastructure. Lead model experimentation, evaluation, fine-tuning, and optimization.

Data & Governance

Establish data strategy for conversational AI.

Required Skills & Experience

6+ years of experience in applied ML/AI or advanced software engineering. Strong expertise in

NLP, LLMs, and conversational AI frameworks

. Proficiency in

Python

, ML libraries (TensorFlow/PyTorch), and NLP packages. Experience with

cloud platforms (AWS/Azure/GCP)

for ML workloads. Hands-on experience deploying ML models into production at scale. Experience with

vector databases (Pinecone, FAISS), retrieval systems, and RAG

. Strong understanding of

MLOps tools

(e.g., Docker, Kubernetes, MLflow). Proven track record leading complex AI initiatives end-to-end.

Conversational AI Development

Build, train, and deploy conversational bots using: LLMs (e.g., GPT, Llama, Claude) NLP/NLU/NLG techniques Dialog management systems Retrieval-augmented generation (RAG) Implement personalization, contextual understanding, and user intent detection. Integrate with business systems (CRM, ticketing, knowledge bases).

Machine Learning Engineering

Lead the full ML lifecycle: data collection & preprocessing feature engineering model training & benchmarking deployment & monitoring Implement MLOps pipelines for automation and continuous improvement.

Data & Governance

Establish data strategy for conversational AI. Manage model versioning, experimentation logs, and performance metrics. Ensure compliance with ethical AI, data privacy, and security requirements.

Required Skills & Experience

6+ years of experience in applied ML/AI or advanced software engineering. Strong expertise in

NLP, LLMs, and conversational AI frameworks

. Proficiency in

Python

, ML libraries (TensorFlow/PyTorch), and NLP packages. Experience with

cloud platforms

Hands-on experience deploying ML models into production at scale. Experience with

vector databases (Pinecone, FAISS), retrieval systems, and RAG

. Strong understanding of

MLOps tools

(e.g., Docker, Kubernetes, MLflow). Proven track record leading complex AI initiatives end-to-end.
The work will be broken into milestones for the employee this will be discussed during the interview period

Job Types: Full-time, Part-time

Pay: From ?60,000.00 per year

Expected hours: 10 - 40 per week

Benefits:

* Work from home