- Clanx
- job, ARA
- Full-Time
- 86 days ago
Senior Applied AI Engineer - Remote.
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Senior Applied AI Engineer - Remote: our view in 3 lines...
- The Role:This role is for a senior applied AI engineer building production machine learning and LLM-powered applications for regulated enterprise workflows.
- The Person:The person will train and fine-tune models, build data processing and inference pipelines, implement MLOps practices, develop production APIs, and monitor and improve model performance.
- Requirements:The ideal candidate has 3+ years of experience in core machine learning, model training, fine-tuning, production deployment, Python, PyTorch, TensorFlow, scikit-learn, AWS, GCP or Azure, Docker, Kubernetes, PostgreSQL, and LLMs.
About the role
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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Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
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3+ years of experience as an AI Engineer, Machine Learning Engineer, Applied AI Engineer, or similar role.
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Strong experience training, fine-tuning, and deploying machine learning models to production.
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Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
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Experience operating and maintaining production ML systems.
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Hands-on experience with AWS, GCP, or Azure cloud platforms.
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Familiarity with cloud ML services such as SageMaker, Vertex AI, or similar platforms.
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Strong understanding of API design and distributed system architecture.
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Experience implementing MLOps practices, CI/CD pipelines, and model monitoring.
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Experience with Docker and Kubernetes.
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Knowledge of PostgreSQL and modern data infrastructure.
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Experience with LLMs, 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
ClanX is a recruitment partner, helping Conqr AI hire an Applied AI Engineer.

