CLANX · Posted 3mo ago
Senior Applied AI Engineer (Fine Tuning) - Remote
- Location
- 🇮🇳 ., India
- Contract
- Full-time
- Role
- ML engineering
- Source
- Employer’s own job board (Recruitee)
Stack
- scikit-learn
- PyTorch
- TensorFlow
- LLM
- Vector DB
- PostgreSQL
- Python
- AWS
- GCP
- Azure
- Kubernetes
- Docker
- CI/CD
The posting
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.