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VOPA Started Hiring
| Role: | AI/ML Engineer |
| Batch: | Recent-Batches |
| Salary: | Up to ₹4.00 – ₹5.00 LPA * |
| Location: | Kothrud/Pune (In-Office) |
| Experience: | Freshers/ Experienced |
| Qualification: | Bachelor’s-Degree/Master’s Degree |
VOPA Off-campus Drive 2026 hiring Freshers For AI/ML Engineer | Bachelor’s Degree
Job Description
About the Role
VOPA Off-campus Drive 2026. We are looking for a passionate and technically strong AI/ML Engineer to join our team.
This is a hands-on engineering role with a research orientation. You will work on fine-tuning open-source models, designing machine learning pipelines, and deploying production-ready AI systems at scale.
Our key focus areas include:
- Handwritten answer evaluation
- Marathi Automatic Speech Recognition (ASR)
- Computer Vision for Indic scripts
- Low-resource language AI models
- Efficient cloud and on-device AI inference
What makes this role exciting?
We have already shipped a fine-tuned vision model (Gemma 4 31B using Unsloth and LoRA) that surpasses many state-of-the-art models on Marathi children’s handwriting recognition.
You will build on this foundation, improve existing systems, and explore new approaches to solving challenging AI problems.
Important: This is not a data annotation or prompt engineering role. We are looking for someone who understands how machine learning models work internally.
Key Responsibilities
1. Model Fine-Tuning & Training
- Fine-tune open-source LLMs and vision models using LoRA, QLoRA, and other Parameter-Efficient Fine-Tuning (PEFT) techniques.
- Work with Hugging Face Transformers, Unsloth, and PEFT libraries.
- Optimize GPU training performance and resource utilization.
- Experiment with model architectures for domain-specific educational applications.
2. Computer Vision & Speech AI
- Develop models for Marathi handwriting recognition and answer evaluation.
- Work on speech recognition systems for Marathi and other Indic languages.
- Design AI-based rubric scoring and evaluation mechanisms.
- Handle noisy, inconsistent, and low-resource real-world datasets.
3. Model Deployment & Optimization
- Deploy fine-tuned models to AWS infrastructure, including ECS/Fargate and GPU inference endpoints.
- Optimize inference performance, latency, throughput, and infrastructure cost.
- Explore quantization, batching, ONNX, TensorRT, and other inference optimization techniques.
- Investigate on-device AI deployment for Android applications.
4. ML Pipelines & Evaluation
- Build end-to-end ML pipelines covering data preprocessing, augmentation, training, evaluation, and serving.
- Define and track evaluation metrics such as Word Error Rate (WER), Character Error Rate (CER), and Devanagari-aware benchmarks.
- Perform structured error analysis to identify model weaknesses.
- Improve model reliability and accuracy through systematic experimentation.
5. Research & Engineering Collaboration
- Read and evaluate recent AI/ML research papers.
- Translate research ideas into practical experiments and production implementations.
- Collaborate with backend engineers to integrate AI models into FastAPI services.
- Contribute to technical decisions regarding model architecture, training, and deployment.
Required Technical Skills
Model Fine-Tuning & Deep Learning
- 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 model 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.
ML Engineering & Programming
- Good programming skills in Python or Rust.
- Proficiency in PyTorch, including autograd, tensor operations, and custom loss functions.
- Experience with Computer Vision (CNNs, image preprocessing, augmentation) and/or Speech AI (CTC, attention-based models, audio feature extraction).
- Understanding of dataset preparation, labeling strategies, and train/validation/test splits.
- Ability to write clean, modular, production-oriented code.
Model Deployment & Inference
- 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.
Preferred Skills (Not Mandatory)
- Experience using Unsloth for efficient model fine-tuning.
- Familiarity with Marathi, Devanagari, or multilingual NLP/ASR systems.
- Experience working with children’s handwriting or speech datasets.
- Knowledge of AWS services such as ECS, S3, CloudFront, and Lambda.
- Exposure to model watermarking, AI model security, or on-device inference protection.
Who Can Apply?
We welcome applications from:
- Freshers with strong practical AI/ML skills and demonstrable projects.
- Engineers with 0–3 years of relevant experience.
- Candidates who have independently fine-tuned or deployed ML models.
- Individuals who enjoy research, experimentation, and solving real-world engineering challenges.
A specific degree or certification is not required.
We value demonstrated technical skills, problem-solving ability, and hands-on experience over academic credentials.
Our Selection Process
Our hiring process is entirely skill-based.
Candidates will be evaluated through a practical technical assessment designed to test their understanding of AI/ML concepts and their ability to solve real engineering problems.
Degrees and certifications will not determine selection.
What We Offer
- Real-world impact: Build AI systems used across 70,000+ schools, reaching millions of children.
- Meaningful engineering challenges: Work on low-resource languages, handwritten text recognition, speech AI, and edge deployment.
- Technical ownership: Take responsibility for research, development, optimization, and deployment.
- Collaborative environment: Work with a technically strong, mission-driven team.
- Growth opportunities: Contribute to AI research and architectural decisions as VOPA scales.High autonomy: We value outcomes, independent thinking, and engineering excellence.
Apply Now
Interested in building AI systems that create meaningful educational impact?
Submit your application through our official careers portal:
About Company
VOPA Off-campus Drive 2026. Vowels of the People Association (VOPA) is a Pune-based organization working at the intersection of Artificial Intelligence and education technology for social impact. Our flagship product, NIPUN Maharashtra, powers foundational literacy and numeracy assessments across 70,000+ schools in Maharashtra, serving 5 million students. We build AI that works for underserved populations — real classrooms, real children, real impact.
VOPA Off-campus Drive 2026 hiring Freshers For AI/ML Engineer | Bachelor’s Degree
How To Apply For The Job?
After checking all the Responsibilities, skills & eligibility criteria, if you are interested and eligible for this role. Then, do apply by the following link
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