Lead Artificial Intelligence Engineer

Lead AI Engineer – Machine Learning

to spearhead the design, development, and deployment of advanced machine learning solutions.

In this leadership role, you will guide a team of AI/ML engineers, contribute hands-on to critical

technical challenges, and collaborate with cross-functional teams to deliver impactful AI

products. This role is ideal for someone who thrives at the intersection of innovation, engineering

rigor, and business value.

Key Responsibilities

Technical Leadership

learning models and AI systems across a range of use cases.

Model Development

learning models using frameworks like PyTorch, TensorFlow, and XGBoost.

Mentorship

culture of innovation, ownership, and continuous learning.

Project Management

ensuring alignment with business objectives and technical feasibility.

System Design

services using cloud-native tools and MLOps best practices.

Collaboration

to translate business problems into AI-driven solutions.

Code Quality & Governance

documentation, versioning, and monitoring.

Innovation

and introduce state-of-the-art solutions where applicable.

Required Skills and Experience

Education

Science, or related technical field

Experience

2+ years in a technical leadership role

Technical Expertise

o Strong programming skills in Python and experience with ML libraries such as

Scikit-learn, TensorFlow, PyTorch, Hugging Face

o Deep understanding of ML fundamentals: feature engineering, model evaluation,

optimization, and deployment

o Proficiency in designing and building data pipelines, real-time processing, and

model inference systems

o Experience with cloud platforms (AWS, GCP, or Azure), containerization

(Docker, Kubernetes), and CI/CD pipelines

o Familiarity with MLOps tools (e.g., MLflow, DVC, Airflow, SageMaker) and

vector databases (e.g., FAISS, Pinecone)

Preferred Qualifications

Hands-on experience with LLMs, RAG pipelines, or generative AI applications

Familiarity with agentic AI frameworks (LangChain, CrewAI, AutoGPT)

Domain expertise in fintech, healthtech, HR tech, or industrial automation

Contributions to open-source AI/ML projects or published research

Knowledge of responsible AI practices, explainability (XAI), and model governance

Soft Skills

Strong leadership and team-building skills

Clear and persuasive communication with both technical and non-technical stakeholders

Strategic thinker with attention to detail and a bias for action