Senior Applied AI/ML Engineer: Build Production AI Tools

Atlas Tech; Georgia; On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive salary

Generous benefits package

Impactful work

Job summary

Atlas Tech in the United States seeks a Senior Applied AI/ML Engineer to design, build, and operationalize advanced AI/ML solutions across mission, ops and business domains. You will lead architectures, select models, develop experiments, and translate complex concepts into production capabilities end users rely on.

Collaboration with product and domain teams is essential. The ideal candidate has strong Python, ML frameworks, and experience deploying in production, including LLMs and end-to-end

Qualifications

• Production deployments of AI/ML models in real systems.
• LLMs, fine-tuning, RAG, or related model training experience.
• Vector databases, embeddings, and semantic search exposure.

Responsibilities

• Design, build, and deploy scalable AI/ML tools for generative use cases.
• Develop end-to-end ML pipelines, including data ingestion and training.
• Implement production-grade inference systems and integrate with apps.
• Lead experiments, evaluate models, and propose improvements.
• Mentor engineers and ensure responsible AI practices.

Skills

Python

ML pipelines

LLM fine-tuning

Prompt engineering

Data ingestion

Model evaluation & monitoring

Communicating with stakeholders

Team leadership

Education

Bachelor's or Master's in Computer Science / ML / Data Science or related field

Tools

TensorFlow

PyTorch

Hugging Face

LangChain

MLflow / SageMaker / Vertex AI

Docker / Kubernetes

Job description

Atlas Tech in the United States seeks a Senior Applied AI/ML Engineer to design, build, and operationalize advanced AI/ML solutions across mission, ops and business domains. You will lead architectures, select models, develop experiments, and translate complex concepts into production capabilities end users rely on.

Collaboration with product and domain teams is essential. The ideal candidate has strong Python, ML frameworks, and experience deploying in production, including LLMs and end-to-end