AI/ML Developer

Growth For Impact; India; On-site; INR 900,000 - 1,800,000; Full time

Job summary

Growth For Impact is seeking a capable AI/ML engineer to design, develop, and deploy scalable AI/ML solutions across operations, manufacturing, supply chain, and enterprise apps. You will build and optimize models, prepare datasets, and create APIs that integrate with ERP and mobile/web systems.

You will collaborate with product managers, stakeholders, and data teams to translate business problems into AI opportunities, monitor performance, and document architectures and pipelines for reliable

Qualifications

• 1–3 years of experience developing AI/ML applications in production environments.
• Experience with Scikit-Learn, TensorFlow, PyTorch, or XGBoost.
• Hands‑on experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
• Strong SQL skills and experience working with structured and unstructured datasets.
• Experience building REST APIs using FastAPI, Flask, or similar frameworks.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience deploying AI solutions into production environments.
• Experience with OCR, document intelligence, or multimodal AI systems.
• Experience with computer vision applications using OpenCV, YOLO, or related frameworks.
• Familiarity with MLOps tools such as MLflow, Airflow, Kubeflow, or similar platforms.
• Experience working with manufacturing, logistics, industrial automation, or supply chain datasets.
• Exposure to IoT, robotics, or sensor data is an added advantage.
• Strong analytical and problem‑solving skills with a first-principles approach.
• Curiosity to experiment with emerging AI technologies while maintaining engineering discipline.
• Ability to independently own AI projects from idea to production deployment.
• Strong communication skills and the ability to explain AI concepts to non‑technical stakeholders.
• Passion for building practical AI solutions that create measurable business impact rather than proof‑of‑concepts.

Responsibilities

• Design, develop, and deploy AI/ML solutions to solve business problems across operations, manufacturing, supply chain, and enterprise applications.
• Develop and optimize machine learning, computer vision, NLP, and predictive analytics models based on business requirements.
• Collaborate with Product Managers and business stakeholders to understand problems, identify AI opportunities, and translate them into scalable solutions.
• Prepare, clean, and engineer datasets for training, evaluation, and production deployment.
• Build APIs and AI services that integrate seamlessly with web applications, mobile applications, ERPs, and enterprise systems.
• Evaluate emerging AI models, frameworks, and technologies to continuously improve solution quality and business impact.
• Monitor model performance, accuracy, latency, and reliability, and continuously improve deployed AI systems.
• Document AI architectures, experiments, and deployment pipelines while following engineering best practices.

Skills

AI/ML development

Python

Scikit-Learn

TensorFlow

PyTorch

XGBoost

SQL

OCR / document intelligence

OpenCV

ML reasoning & problem solving

Communication with stakeholders

Tools

LangChain

LangGraph

LlamaIndex

FastAPI

Flask

MLflow

Airflow

Kubeflow

YOLO

OpenCV

AWS

Azure

GCP

Job description

ROLE

• Design, develop, and deploy AI/ML solutions to solve business problems across operations, manufacturing, supply chain, and enterprise applications.


• Develop and optimize machine learning, computer vision, NLP, and predictive analytics models based on business requirements.


• Collaborate with Product Managers and business stakeholders to understand problems, identify AI opportunities, and translate them into scalable solutions.


• Prepare, clean, and engineer datasets for training, evaluation, and production deployment.


• Build APIs and AI services that integrate seamlessly with web applications, mobile applications, ERPs, and enterprise systems.


• Evaluate emerging AI models, frameworks, and technologies to continuously improve solution quality and business impact.


• Monitor model performance, accuracy, latency, and reliability, and continuously improve deployed AI systems.


• Document AI architectures, experiments, and deployment pipelines while following engineering best practices.

REQUIREMENTS

• 1–3 years of experience developing AI/ML applications in production environments.


• Experience with machine learning libraries such as Scikit-Learn, TensorFlow, PyTorch, or XGBoost.


• Hands‑on experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.


• Strong SQL skills and experience working with structured and unstructured datasets.


• Experience building REST APIs using FastAPI, Flask, or similar frameworks.


• Familiarity with cloud platforms such as AWS, Azure, or GCP.


• Experience deploying AI solutions into production environments.


• Experience with OCR, document intelligence, or multimodal AI systems.


• Experience with computer vision applications using OpenCV, YOLO, or related frameworks.


• Familiarity with MLOps tools such as MLflow, Airflow, Kubeflow, or similar platforms.


• Experience working with manufacturing, logistics, industrial automation, or supply chain datasets.


• Exposure to IoT, robotics, or sensor data is an added advantage.


• Strong analytical and problem‑solving skills with a first-principles approach.


• Curiosity to experiment with emerging AI technologies while maintaining engineering discipline.


• Ability to independently own AI projects from idea to production deployment.


• Strong communication skills and the ability to explain AI concepts to non‑technical stakeholders.


• Passion for building practical AI solutions that create measurable business impact rather than proof‑of‑concepts.