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CLANX · Posted 3mo ago

Senior Applied AI Engineer (Fine Tuning) - Remote

RemoteSenior
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.