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JobsVowels of the People Association (VOPA)AI/ML Engineer

Vowels of the People Association (VOPA)

AI/ML Engineer

Verified

On-Site

Full-Time

0–3 Years

Location

Pune

Salary

₹4–5 LPA

Posted

1h ago

Applicants

6

How to applyApply through the Apply button

About the role

Apply through the official VOPA careers portal: https://careers.vopa.in/jobs/ai-ml-engineer-38 Vowels of the People Association (VOPA) is hiring an AI/ML Engineer in Kothrud, Pune, for a full-time, i… Subscribe to Premium to view the full description and apply.

Responsibilities

Fine-tune open-source language and vision models using LoRA, QLoRA, and other parameter-efficient fine-tuning techniques.
Work with Hugging Face Transformers, Unsloth, and PEFT libraries.
Optimize GPU training performance and resource utilization.
Experiment with model architectures for educational applications.

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Develop models for Marathi handwriting recognition and answer evaluation.

Build speech recognition systems for Marathi and other Indic languages.

Design AI-based rubric scoring and evaluation mechanisms.

Handle noisy, inconsistent, and low-resource datasets.

Deploy fine-tuned models to AWS infrastructure, including ECS/Fargate and GPU inference endpoints.

Optimize inference latency, throughput, performance, and infrastructure cost.

Explore quantization, batching, ONNX, TensorRT, and on-device AI deployment.

Build end-to-end ML pipelines for preprocessing, augmentation, training, evaluation, and serving.

Track metrics such as Word Error Rate (WER), Character Error Rate (CER), and Devanagari-aware benchmarks.

Conduct structured error analysis and improve model reliability through experimentation.

Review AI/ML research papers and translate relevant ideas into practical implementations.

Collaborate with backend engineers to integrate models into FastAPI services.

Contribute to technical decisions involving model architecture, training, and deployment.

Requirements

Strong understanding of Transformer architectures, attention mechanisms, embeddings, and positional encoding.
Knowledge of encoder, decoder, and encoder-decoder architectures.
Hands-on experience with LoRA/QLoRA fine-tuning using Hugging Face PEFT or Unsloth.
Understanding of quantization techniques such as NF4, GPTQ, and AWQ.
Familiarity with learning rate scheduling, gradient accumulation, and mixed-precision training.
Ability to diagnose training instability, loss spikes, and gradient-related issues.

Required Skills

PythonRustPyTorchTransformer ArchitecturesDeep LearningLLM Fine-TuningLoRAQLoRAPEFTHugging Face TransformersUnslothModel QuantizationComputer VisionSpeech RecognitionAutomatic Speech RecognitionNatural Language ProcessingMachine Learning PipelinesModel EvaluationDockerAWS

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Employer profile

About Vowels of the People Association (VOPA)

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Frequently Asked Questions

What is the salary for AI/ML Engineer?

The listed salary for AI/ML Engineer at Vowels of the People Association (VOPA) is ₹4–5 LPA.

Where is this AI/ML Engineer role located?

This position is based in Pune (On-Site).

What experience is required for AI/ML Engineer?

Candidates are expected to have 0–3 Years of experience for this role.

How do I apply for AI/ML Engineer at Vowels of the People Association (VOPA)?

Use the Apply button on this HireDoor job page to submit your application for AI/ML Engineer at Vowels of the People Association (VOPA).

Good programming skills in Python or Rust.

Proficiency in PyTorch, including autograd, tensor operations, and custom loss functions.

Experience with computer vision techniques such as CNNs, image preprocessing, and augmentation, and/or speech AI techniques such as CTC, attention-based models, and audio feature extraction.

Understanding of dataset preparation, labeling strategies, and train/validation/test splits.

Ability to write clean, modular, production-oriented code.

Experience deploying ML models using Docker and cloud infrastructure.

Familiarity with GPU-based inference environments.

Understanding of inference optimization, batching, ONNX, TensorRT, and KV caching.

Awareness of model size, latency, and runtime constraints for edge devices.

Ability to balance inference cost, latency, and throughput.

ECS

Fargate

GPU Inference

FastAPI

ONNX

TensorRT

Model Optimization

Data Preprocessing

Data Augmentation

Model Deployment

SQL

Devanagari NLP

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AI/ML Engineer at Vowels of the People Association (VOPA) | HireDoor