Lead Artificial Intelligence Engineer

3 weeks ago

india, IN TalentXM Full time

We are looking for a visionary and technically skilled 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: Lead the architecture, development, and deployment of machine

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

Model Development: Design, train, and optimize supervised, unsupervised, and deep

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

Mentorship: Coach and mentor a team of ML engineers and data scientists; foster a

culture of innovation, ownership, and continuous learning.

Project Management: Drive planning, execution, and delivery of AI/ML projects,

ensuring alignment with business objectives and technical feasibility.

System Design: Architect scalable, secure, and high-performance ML pipelines and

services using cloud-native tools and MLOps best practices.

Collaboration: Work closely with product managers, data engineers, and DevOps teams

to translate business problems into AI-driven solutions.

Code Quality & Governance: Establish standards for model quality, reproducibility,

documentation, versioning, and monitoring.

Innovation: Stay current with research and industry trends in ML/AI, evaluate new tools,

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


Required Skills and Experience

Education: Bachelor’s or Master’s in Computer Science, Machine Learning, Data

Science, or related technical field

Experience: 6–10+ years of experience in software engineering or AI/ML, with at least

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

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