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
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3+ years of overall experience as an AI Engineer
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Strong hands-on experience with fine-tuning AI/ML models for production use cases.
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Experience with LLM fine-tuning, including model selection, dataset preparation, training, evaluation, and optimization.
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Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
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Experience deploying and maintaining fine-tuned models in production environments.
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Familiarity with techniques such as LoRA, QLoRA, PEFT, and parameter-efficient fine-tuning.
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Experience working with model evaluation, monitoring, and performance optimization.
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Hands-on experience with AWS, GCP, or Azure cloud platforms.
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Experience with Docker, Kubernetes, CI/CD, and MLOps practices.
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Strong understanding of APIs and distributed system architecture.
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Knowledge of PostgreSQL and modern data infrastructure.
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Experience with RAG systems and vector databases is a strong plus.
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Excellent written and verbal communication skills in English.
Responsibilities
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Own end-to-end delivery of production AI and ML systems from experimentation to deployment.
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Train, fine-tune, and optimize machine learning models, including LLMs and open-weight models.
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Build and maintain training, data processing, and inference pipelines.
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Improve model performance across accuracy, latency, reliability, and cost.
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Implement MLOps best practices for deployment, monitoring, CI/CD, and automated retraining.
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Develop evaluation frameworks, benchmark datasets, and quality checks for production models.
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Design and maintain scalable APIs and services that expose AI capabilities.
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Collaborate with Product, Backend, and Frontend teams to integrate AI into customer-facing workflows.
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Monitor production systems and continuously improve model and infrastructure performance.
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Research and evaluate emerging AI techniques, tools, and frameworks.
Job Details
Location: Remote
Interview Process
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Recruiter Screening
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Hiring Manager Discussion
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Applied AI Technical Assessment
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Founder Round
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Final HR Discussion
Important Note
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