Job highlights

- What matters most is strong real-world AI / ML experience

In this role, youll experiment, architect, and build AI/ML solutions that transform learning experiences at scale, mentor engineers, and shape strategy that drives learning outcomes and equity for all. > What Youll Be Doing>
- You will Experiment, Architect Build AI solutions for learning at scale, focusing on compact, efficient models optimized for client-side, low-resource applications. You will Design, fine-tune deploy lightweight LLMs and transformer-based models (DistilBERT, TinyGPT, instruction-tuned open-source models) for real-world learning applications.>
- You will establish AI-driven evaluation and feedback frameworks to measure model performance, optimize resource usage, and enhance learning outcomes. This includes implementing automated benchmarking, A/B testing, and human-in-the-loop feedback for continuous improvement.>
- You are committed to a careful, iterative, and data-driven approach optimizing models for speed, memory footprint, and on-device inference, while ensuring ethical, reliable, and high-quality AI solutions. You also have experience in creating evaluation datasets and metrics for fine-tuned, lightweight models.>
- You will create effective prompt and chain flows, build reusable templates, and integrate models with client-side apps, APIs, or edge devices using FastAPI, Flask, or mobile deployment frameworks.>
- You will mentor junior engineers,



guide them in efficient experimentation, lightweight model design, and rapid prototyping, and ensure production-ready, well-tested code with typing, pytest, packaging, and thorough documentation..>

What Were Looking For. >
- Expert-level programming in Python with strong foundations in data structures, algorithms, and scalable software design.>
- Deep understanding of ML and deep learning algorithms CNNs, RNNs, Transformers, and LLMs with experience optimizing models for lightweight and client-side applications.>
- Hands-on expertise with PyTorch, TensorFlow, and Hugging Face, along with familiarity with ML workflow tools like MLFlow, TFX, and ONNX.>
- Proficiency in data preprocessing, feature engineering, model tuning, and designing efficient evaluation benchmarks for edge and mobile deployment.>
- A strategic mindset with hands-on execution ability you can design architecture as well as roll up your sleeves and code.>
- A lifelong learner who stays informed about emerging AI research, contributes to open-source projects, and understands their impact on real-world learning systems.>

Years of experience: > We are hiring at all levels, from engineers with 2+ years of experience to senior leadership/CTO. What matters most is strong real-world AI/ML experience. If you meet 60 percent of the technical requirements, enjoy learning (Bonus points if you had excellent Math scores

📌 ML engineer (Nashik)
🏢 Navgurukul Foundation For Social Welfare
📍 Nashik