Salary
≈ $7k – $18k per year (Estimated)
Location
In office (Noida)
Seniority
Junior · 1+ year exp
Employment
Full-Time
Confirmed on the employer's own hiring board on Oct 26, 2026. First seen by Alion on Aug 14, 2026. Attero Recycling scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Attero is an electronic asset management company that promotes the reuse and recycling of electronics sustainably by offering a range of recycling plants for recovering reusable resources and precious metals.
Backed by Kalaari Capital
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.
Qualifications & Skills Required
Education
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field (B.Tech./B.E. preferred).
Experience
- 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.
Technical Skills
- 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
Preferred Qualifications
- 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.
What We’re Looking For
- 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.
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