Skip to content
CLANX

Senior Applied AI Engineer (Fine Tuning) - Remote

., Mahārāshtra, IndiaRemote · India
Senior · fulltime_permanent · Engineering
POSTED 11 JULVERIFIED 20H AGO
Apply Ask
Role
120 days opentrue age
Posted 11 Jul
Pay
₹33.4L–₹43.7Lno pay posted
Market p25–p75
₹33.4L–₹43.7L
India · n=6 · 365d to 6 Nov
CompanyCLANX →
29open roles
Opened · 30d
+0
Closed · 30d
−0
2d of snapshots · 30d window
Market
1,510open · Senior ML / AI
All ml / ai
6,685open
All tracked boards · live 8 Nov · n=1,510
PythonPostgreSQLAWSGCPAzureKubernetesDockerPyTorchTensorFlowLLMsDistributed systems

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.

Source · CLANXFirst seen 4 NovOriginal ↗