The Role
Design, develop, and deploy production AI/ML solutions using machine learning, LLMs, RAG, AI agents, computer vision, NLP, and predictive analytics. Prepare datasets, build APIs and enterprise integrations, monitor model performance, evaluate emerging technologies, and document architectures and deployment pipelines. Collaborate with product managers, engineers, and business stakeholders to translate operational challenges into scalable AI systems across manufacturing, supply chain, recycling, and enterprise workflows.
Summary Generated by Built In
Job Title: AI/ML Developer
Location: Noida
As an AI/ML Developer, you will be responsible for designing, building, and deploying AI-powered solutions that solve real business problems across manufacturing, supply chain, operations, recycling, and enterprise workflows. You will work closely with Product Managers, Engineering, and business teams to convert operational challenges into production-ready AI systems.
This role requires someone who enjoys solving complex problems using machine learning, LLMs, computer vision, and data engineering rather than simply experimenting with models.
Key Responsibilities- Design, develop, and deploy AI/ML solutions to solve business problems across operations, manufacturing, supply chain, and enterprise applications.
- Build production-grade applications using Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI agents, and modern AI frameworks.
- 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.
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field (B.Tech./B.E. preferred).
- 1–3 years of experience developing AI/ML applications in production environments.
- Strong hands-on experience with Python (mandatory).
- Experience with machine learning libraries such as Scikit-Learn, TensorFlow, PyTorch, or XGBoost.
- Experience building applications using modern LLMs (OpenAI, Claude, Gemini, Llama, etc.).
- 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.
- Python
- Machine Learning
- Deep Learning
- Generative AI
- Large Language Models (LLMs)
- Retrieval Augmented Generation (RAG)
- AI Agents
- Prompt Engineering
- NLP
- Computer Vision
- Vector Databases
- SQL
- Git
- Docker
- API Development
- 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.
Skills Required
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field; B.Tech./B.E. preferred.
- 1–3 years of experience developing AI/ML applications in production environments.
- Strong hands-on experience with Python.
- Experience with Scikit-Learn, TensorFlow, PyTorch, or XGBoost.
- Experience building applications with modern LLMs such as OpenAI, Claude, Gemini, or Llama.
- Hands-on experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
- Strong SQL skills and experience with structured and unstructured datasets.
- Experience building REST APIs using FastAPI, Flask, or similar frameworks.
- Familiarity with AWS, Azure, or GCP.
- Experience deploying AI solutions into production environments.
- Experience with OCR, document intelligence, or multimodal AI systems.
- Experience with OpenCV, YOLO, or related computer vision frameworks.
- Familiarity with MLflow, Airflow, Kubeflow, or similar MLOps platforms.
- Experience with manufacturing, logistics, industrial automation, or supply chain datasets.
- Exposure to IoT, robotics, or sensor data.
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Attero is an India-based climate-technology company specializing in advanced recycling of electronic waste and lithium-ion batteries. It offers e-waste management, battery recycling, and eco-friendly disposal solutions while recovering valuable green metals and other resources from discarded materials. Attero advances sustainable resource recovery and helps reduce waste by applying deep-technology recycling to support a circular economy at industrial scale through its operations.
