# Senior Applied AI Engineer (Fine Tuning) - Remote at CLANX > Remote · India · Senior · ML / AI · open. Source: https://alderhq.app/jobs/recruitee%3Aclanx%3A2674466 (read 2026-11-08). ## Facts (observed) - Company: [CLANX](https://alderhq.app/companies/clanx) - Location text: ., Mahārāshtra, India - Where it can be done from (inferred): Remote · India (evidence: "Location lists "india" and remote") - Posted: 2026-07-11 (120 days ago) - First seen by alder: 2026-11-04 · last verified: 2026-11-07 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.clanx.ai/o/senior-applied-aiengineer-remote - Skills listed (inferred): Python, PostgreSQL, AWS, GCP, Azure, Kubernetes, Docker, PyTorch, TensorFlow, LLMs, Distributed systems ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (India, n 6): p25 ₹33.4L, median ₹38.8L, p75 ₹43.7L ## Description (the employer's text) Applied AI Engineer with 3+ years of experience in core machine learning, model training, fine-tuning, and production deployment, building scalable AI systems and LLM-powered applications. ### Company Details Conqr AI is an early-stage startup building AI solutions for regulated, document-heavy professional workflows. The company focuses on privacy, security, reliability, and delivering high-impact AI products for enterprise users. Website: https://www.conqr.ai/ ### Requirements 3+ years of overall experience as an AI Engineer Strong hands-on experience with fine-tuning AI/ML models for production use cases. Experience with LLM fine-tuning, including model selection, dataset preparation, training, evaluation, and optimization. Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and scikit-learn. Experience deploying and maintaining fine-tuned models in production environments. Familiarity with techniques such as LoRA, QLoRA, PEFT, and parameter-efficient fine-tuning. Experience working with model evaluation, monitoring, and performance optimization. Hands-on experience with AWS, GCP, or Azure cloud platforms. Experience with Docker, Kubernetes, CI/CD, and MLOps practices. Strong understanding of APIs and distributed system architecture. Knowledge of PostgreSQL and modern data infrastructure. Experience with RAG systems and vector databases is a strong plus. Excellent written and verbal communication skills in English. ### Responsibilities Own end-to-end delivery of production AI and ML systems from experimentation to deployment. Train, fine-tune, and optimize machine learning models, including LLMs and open-weight models. Build and maintain training, data processing, and inference pipelines. Improve model performance across accuracy, latency, reliability, and cost. Implement MLOps best practices for deployment, monitoring, CI/CD, and automated retraining. Develop evaluation frameworks, benchmark datasets, and quality checks for production models. Design and maintain scalable APIs and services that expose AI capabilities. Collaborate with Product, Backend, and Frontend teams to integrate AI into customer-facing workflows. Monitor production systems and continuously improve model and infrastructure performance. Research and evaluate emerging AI techniques, tools, and frameworks. ### Job Details Location: Remote ### Interview Process Recruiter Screening Hiring Manager Discussion Applied AI Technical Assessment Founder Round Final HR Discussion ### Important Note ClanX is a recruitment partner, helping Conqr AI hire an Applied AI Engineer. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/recruitee%3Aclanx%3A2674466 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.