We're Hiring
Machine Learning Engineer (4+ yrs)
Gift City, Gandhinagar|4–5 Years Experience|Work from Office|Full Time
We are seeking an experienced Machine Learning Engineer to join our team and drive the development of production-grade AI systems. This role requires deep expertise in Retrieval-Augmented Generation (RAG), natural language to SQL conversion, and large language model fine-tuning. You will be responsible for building, deploying, and maintaining sophisticated ML systems that power our products.
Key Responsibilities
- Design and implement production-ready RAG pipelines for knowledge-intensive applications
- Build and optimize text-to-SQL engines that translate natural language queries into executable SQL code
- Develop, train, and fine-tune smaller language models for specific domain applications
- Fine-tune large language models (LLMs) using various techniques including supervised fine-tuning, RLHF, and parameter-efficient methods
- Deploy and maintain ML models in production environments with monitoring, versioning, and continuous improvement
- Optimize model performance, latency, and cost for real-world applications
- Collaborate with cross-functional teams to integrate ML capabilities into products
- Establish best practices for ML ops, model evaluation, and deployment pipelines
- Stay current with latest developments in LLMs, RAG architectures, and ML tooling
Required Qualifications
Experience
- 4–5 years of hands-on experience in machine learning engineering
- Proven track record of building and deploying ML systems in production environments
- Experience with the full ML lifecycle from data preparation to production deployment
Technical Skills - RAG & Information Retrieval
- Deep understanding of RAG architecture and implementation
- Experience with vector databases (Pinecone, Weaviate, Chroma, FAISS, etc.)
- Knowledge of embedding models and semantic search techniques
- Experience with chunking strategies, retrieval optimization, and context management
Technical Skills - Text-to-SQL Systems
- Strong experience building natural language to SQL conversion systems
- Understanding of database schemas, query optimization, and SQL dialects
- Experience with few-shot prompting and query validation techniques
Technical Skills - LLM Development & Fine-tuning
- Hands-on experience fine-tuning LLMs (GPT, Llama, Mistral, etc.)
- Knowledge of fine-tuning techniques: full fine-tuning, LoRA, QLoRA, prefix tuning
- Experience training smaller language models from scratch or adapting existing ones
- Understanding of model quantization, distillation, and compression techniques
Technical Skills - Production ML Systems
- Strong software engineering skills with production-level code quality
- Experience with ML ops tools and practices (MLflow, Weights & Biases, etc.)
- Knowledge of containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure)
- Experience with API development and deployment (FastAPI, Flask, etc.)
- Understanding of monitoring, logging, and debugging production ML systems
Technical Skills - Programming & Tools
- Expert-level Python programming
- Proficiency with PyTorch or TensorFlow
- Experience with Hugging Face Transformers, LangChain, or LlamaIndex
- Familiarity with SQL and database technologies
- Version control with Git and collaborative development workflows
Additional Requirements
- Strong problem-solving and analytical skills
- Excellent communication skills and ability to explain complex technical concepts
- Experience working in agile development environments
- Bachelor's or Master's degree in Computer Science, Machine Learning, or related field (or equivalent practical experience)
Preferred Qualifications
- Experience with prompt engineering and advanced prompting techniques
- Knowledge of reinforcement learning from human feedback (RLHF)
- Familiarity with evaluation frameworks for LLM applications
- Experience with data annotation and synthetic data generation
- Publications or contributions to open-source ML projects
- Experience with A/B testing and experimentation in production
- Understanding of model safety, bias mitigation, and responsible AI practices
Interested in this role?
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