AI/ML Tech Lead

Konstant Infosolutions Pvt. Ltd.; Jaipur; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Konstantinfo is seeking an AI/ML Tech Lead to provide hands‑on technical leadership across AI and ML engineering projects. You will guide teams from solution design through production deployment, set engineering standards, review code and architecture, and mentor engineers to deliver high‑quality, scalable AI systems.

The role covers model and training‑pipeline decisions, evaluation practices, inference infrastructure, and integration with product requirements.

Qualifications

• 5+ years of experience in software engineering, machine learning, AI engineering, or data science.
• 1+ years of experience leading AI/ML technical delivery, mentoring engineers, or owning architecture decisions.
• Strong proficiency in Python and ML frameworks including PyTorch, TensorFlow, Scikit‑learn, or Hugging Face.
• Experience deploying ML, NLP, computer vision, LLM, RAG, or agentic AI solutions in production.
• Solid understanding of ML lifecycle management: data preparation, training, evaluation, deployment, monitoring, and retraining.
• Experience with MLOps or LLMOps tools and practices, including model versioning, CI/CD, experiment tracking, and observability.
• Knowledge of cloud infrastructure, containers, APIs, distributed systems, databases, queues, and caching.
• Strong technical communication skills, with the ability to explain trade‑offs to technical and non‑technical stakeholders.
• Proven ability to lead code reviews, system design discussions, and technical problem‑solving across delivery teams.
• Experience with AI agents, multi‑agent systems, LLM fine‑tuning, and GenAI evaluation frameworks.
• Familiarity with Kubernetes, Terraform, Airflow, Kubeflow, MLflow, LangSmith, or equivalent platforms.
• Experience working in client‑facing delivery environments or across multiple concurrent AI projects.
• Contributions to open‑source AI/ML projects, technical blogs, research, or internal engineering standards.

Responsibilities

• Lead the technical design, development, deployment, and maintenance of AI/ML and Generative AI applications.
• Define engineering standards for model development, code quality, testing, documentation, model evaluation, and production deployment.
• Provide technical direction for ML pipelines, data processing, feature engineering, model serving, RAG systems, and AI agents.
• Conduct architecture reviews, design reviews, code reviews, and technical risk assessments across projects.
• Mentor AI/ML engineers and support their growth through technical guidance, feedback, and knowledge-sharing.
• Partner with product managers, architects, data teams, and business stakeholders to translate goals into technical plans.
• Drive decisions on frameworks, model selection, infrastructure, deployment approaches, and performance optimization.
• Ensure models and AI services meet requirements for quality, reliability, security, scalability, latency, and cost.
• Establish model monitoring, observability, experiment tracking, evaluation, retraining, and incident‑response practices.
• Identify technical bottlenecks, manage technical debt, and create practical delivery roadmaps for the team.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

Hugging Face

MLOps

LLMOps

Technical communication

Tools

Kubernetes

Terraform

Airflow

Kubeflow

MLflow

LangSmith

Job description

Job Description:

We are looking for an AI/ML Tech Lead to provide hands‑on technical leadership across AI and machine‑learning engineering projects. You will guide teams from solution design through production deployment, set engineering standards, review code and architecture, mentor engineers, and ensure delivery of high‑quality, scalable AI systems. AI/ML technical leads typically own technical direction, model and training‑pipeline decisions, evaluation practices, inference infrastructure, and the integration of ML capabilities with product requirements.

Requirements and Duties:

Lead the technical design, development, deployment, and maintenance of AI/ML and Generative AI applications.Define engineering standards for model development, code quality, testing, documentation, model evaluation, and production deployment.Provide technical direction for ML pipelines, data processing, feature engineering, model serving, RAG systems, and AI agents.Conduct architecture reviews, design reviews, code reviews, and technical risk assessments across projects.Mentor AI/ML engineers and support their growth through technical guidance, feedback, and knowledge-sharing.Partner with product managers, architects, data teams, and business stakeholders to translate goals into technical plans.Drive decisions on frameworks, model selection, infrastructure, deployment approaches, and performance optimization.Ensure models and AI services meet requirements for quality, reliability, security, scalability, latency, and cost.Establish model monitoring, observability, experiment tracking, evaluation, retraining, and incident‑response practices.Identify technical bottlenecks, manage technical debt, and create practical delivery roadmaps for the team.

Skill and Ability:

5+ years of experience in software engineering, machine learning, AI engineering, or data science.1+ years of experience leading AI/ML technical delivery, mentoring engineers, or owning architecture decisions.Strong proficiency in Python and ML frameworks including PyTorch, TensorFlow, Scikit‑learn, or Hugging Face.Experience building and deploying ML, NLP, computer vision, LLM, RAG, or agentic AI solutions in production.Solid understanding of ML lifecycle management: data preparation, training, evaluation, deployment, monitoring, and retraining.Experience with MLOps or LLMOps tools and practices, including model versioning, CI/CD, experiment tracking, and observability.Knowledge of cloud infrastructure, containers, APIs, distributed systems, databases, queues, and caching.Strong technical communication skills, with the ability to make and explain trade‑offs to technical and non‑technical stakeholders.Proven ability to lead code reviews, system design discussions, and technical problem‑solving across delivery teams.Experience with AI agents, multi‑agent systems, LLM fine‑tuning, and GenAI evaluation frameworks.Familiarity with Kubernetes, Terraform, Airflow, Kubeflow, MLflow, LangSmith, or equivalent platforms.Experience working in client‑facing delivery environments or across multiple concurrent AI projects.Contributions to open‑source AI/ML projects, technical blogs, research, or internal engineering standards.

Current Openings

We consider each team member as a part of our family. Our work culture is rooted in transparency, meaningful collaboration, and inclusivity. Explore career opportunities and find the role that fits your skills.

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